Project Engineer Jobs - Amman Jordan

<p><h4>Description</h4> <p>Mindrift is looking for highly skilled senior Python data scraping engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.</p> <p>In this role, as an AI pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.</p> <p>This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction, and processing.</p> <h4>What we do</h4> <p>The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of generative AI by tapping into real-world expertise from across the globe.</p> <p>This is a freelance role for a Tendem project. As a senior Python data scraping engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.</p> <h4>Key responsibilities:</h4> <ul> <li>Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.</li> <li>Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.</li> <li>Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.</li> <li>Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.</li> <li>Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.</li> </ul> <h4>Requirements:</h4> <ul> <li>At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).</li> <li>Bachelor’s or master’s degree in engineering, applied mathematics, computer science, or related technical fields is a plus.</li> <li>Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows. We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.</li> <li>Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.</li> <li>Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).</li> <li>Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).</li> <li>Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale.</li> <li>Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows.</li> <li>Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks.</li> <li>Strong attention to detail and commitment to data accuracy.</li> <li>Self-directed work ethic with ability to troubleshoot independently.</li> <li>English proficiency: upper-intermediate (B2) or above (required).</li> </ul> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $25 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Description</h4> <p>Mindrift is looking for highly skilled senior Python data scraping engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.</p> <p>In this role, as an AI pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.</p> <p>This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction, and processing.</p> <h4>What we do</h4> <p>The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of generative AI by tapping into real-world expertise from across the globe.</p> <p>This is a freelance role for a Tendem project. As a senior Python data scraping engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.</p> <h4>Key responsibilities:</h4> <ul> <li>Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.</li> <li>Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.</li> <li>Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.</li> <li>Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.</li> <li>Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.</li> </ul> <h4>Requirements:</h4> <ul> <li>At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).</li> <li>Bachelor’s or master’s degree in engineering, applied mathematics, computer science, or related technical fields is a plus.</li> <li>Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows. We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.</li> <li>Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.</li> <li>Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).</li> <li>Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).</li> <li>Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale.</li> <li>Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows.</li> <li>Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks.</li> <li>Strong attention to detail and commitment to data accuracy.</li> <li>Self-directed work ethic with ability to troubleshoot independently.</li> <li>English proficiency: upper-intermediate (B2) or above (required).</li> </ul> <p>A link to GitHub is a plus.</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $25 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Description</h4> <p>We are hiring a cybersecurity consultant / sales engineer for a remote, client-facing role based in Amman, Jordan.</p> <p>This role is suitable for someone with 1–3 years of experience in sales, pre-sales, business development, or consulting, with a cybersecurity background or strong technical understanding of cybersecurity services.</p> <p>The role will focus on engaging with clients, understanding their cybersecurity needs, explaining services clearly, qualifying opportunities, following up with prospects, updating CRM activities, and supporting business growth.</p> <p>This is not a pure technical delivery role and not a general sales role. It is a consultative cybersecurity role for someone who can combine communication skills, cybersecurity understanding, and commercial discipline.</p> <p>The ideal candidate should be comfortable speaking with clients, asking the right questions, identifying business needs, and supporting the sales process for cybersecurity services such as SOC, GRC, VAPT, compliance, and advisory services.</p> <h4>Requirements</h4> <ul> <li>Currently based in Amman, Jordan</li> <li>1–3 years of experience in sales, pre-sales, business development, or consulting</li> <li>Experience selling or supporting services, not only products or software licenses</li> <li>Cybersecurity background or strong technical understanding of cybersecurity services</li> <li>Previous exposure to cybersecurity services such as SOC, GRC, VAPT, compliance, advisory, or managed security services is preferred</li> <li>Strong communication and follow-up skills</li> <li>Comfortable speaking with clients and explaining cybersecurity services clearly</li> <li>Comfortable working with monthly sales targets and pipeline updates</li> <li>Experience using HubSpot or any CRM system is preferred</li> <li>Ability to work remotely with discipline, daily follow-up, and proper activity reporting</li> <li>Stable internet connection and a professional environment for client calls</li> <li>Arabic and English communication skills are required</li> </ul> <h4>Benefits</h4> <ul> <li>Remote work model</li> <li>Opportunity to grow in cybersecurity sales, consulting, and business development</li> <li>Exposure to enterprise cybersecurity services and client engagements</li> <li>Clear role focus with structured pipeline and CRM activity</li> <li>Opportunity to work with an experienced cybersecurity team</li> <li>Professional growth in areas such as SOC, GRC, VAPT, compliance, and advisory services</li> <li>Performance-driven environment with room for career development</li> </ul></p><p></p>

<p><h4>About Lucidya<\/h4>\n<p>Lucidya is building the next generation of AI-powered customer experience solutions for enterprises across the MENA region. Our new AI Agents business line focuses on deploying intelligent, enterprise-grade AI agents that automate, assist, and augment customer-facing and operational workflows - securely, reliably, and at scale.<\/p>\n<p>This role sits at the heart of turning AI agent concepts into live, business-impacting solutions.<\/p>\n<h4>About the Role<\/h4>\n<p>The Project \/ Delivery Manager owns one critical question:<\/p>\n<p><strong>\"How do we execute what we promised?\"<\/strong><\/p>\n<p>You take the Solution Consultant\u2019s vision and turn it into a clear execution plan, structured backlog, and predictable delivery rhythm - from initial scoping through go-live and stabilization.<\/p>\n<p>You are the operational backbone of AI agent pilots and enterprise deployments, ensuring alignment across clients, engineering, data, and AI teams while keeping delivery on track.<\/p>\n<h4>Key Responsibilities<\/h4>\n<ol>\n <li><strong>Scoping & Handover from Solution Consultant<\/strong>\n <p>You step in once a pilot or project is conceptually approved.<\/p>\n <p><strong>Formal Handover<\/strong><\/p>\n <p>Receive full delivery context, including:<\/p>\n <ul>\n <li>Discovery findings<\/li>\n <li>Workflow maps and agent logic<\/li>\n <li>Success criteria and KPIs<\/li>\n <li>Pilot narrative and client expectations<\/li>\n <\/ul>\n <p>Clarify:<\/p>\n <ul>\n <li>Scope, constraints, dependencies, and assumptions<\/li>\n <li>Technical and operational boundaries<\/li>\n <\/ul>\n <p><strong>Scope Confirmation<\/strong><\/p>\n <p>Translate high-level workflows into clear delivery components:<\/p>\n <ul>\n <li>AI Agent versions (v0, v1, v2\u2026)<\/li>\n <li>Integrations, channels, and data sources<\/li>\n <li>Dashboards, reporting, and monitoring<\/li>\n <li>Training, enablement, and documentation<\/li>\n <\/ul>\n <p>Align internally and with the client on:<\/p>\n <ul>\n <li>What is in scope vs out of scope for each phase<\/li>\n <\/ul>\n <\/li>\n <li><strong>Detailed Planning & Backlog Management<\/strong>\n <p>This is where ideas become execution.<\/p>\n <p>You own:<\/p>\n <ul>\n <li><strong>Building the delivery plan and timeline:<\/strong><\/li>\n <ul>\n <li>Milestones, sprints, and go-live checkpoints<\/li>\n <li>Cross-team dependencies (AI, backend, integrations, data, CX ops)<\/li>\n <\/ul>\n <li><strong>Creating and maintaining the delivery backlog:<\/strong><\/li>\n <ul>\n <li>Break down deliverables into tasks and subtasks<\/li>\n <li>Assign clear owners (AI Agent Engineers, Backend, Frontend, Data, Solutions)<\/li>\n <\/ul>\n <li><strong>Keeping tools accurate and trusted:<\/strong><\/li>\n <ul>\n <li>Trello \/ Jira \/ Notion as the single source of truth<\/li>\n <li>Task status, blockers, due dates, and changes<\/li>\n <\/ul>\n <\/ul>\n <\/li>\n <li><strong>Coordination & Day-to-Day Execution<\/strong>\n <p>You are the operational heartbeat of each pilot or project.<\/p>\n <p>Responsibilities include:<\/p>\n <ul>\n <li>Running regular execution cadences:<\/li>\n <ul>\n <li>Standups and check-ins<\/li>\n <li>Progress reviews and decision syncs<\/li>\n <\/ul>\n <li>Ensuring tight collaboration between:<\/li>\n <ul>\n <li>Solution Consultants (business & workflows)<\/li>\n <li>Engineering and AI teams (implementation)<\/li>\n <li>Client stakeholders (CX, IT, Operations, Compliance)<\/li>\n <\/ul>\n <li>Driving execution discipline:<\/li>\n <ul>\n <li>Clear meeting notes<\/li>\n <li>Action items with owners and deadlines<\/li>\n <li>Relentless follow-up until closure<\/li>\n <\/ul>\n <\/ul>\n <\/li>\n <li><strong>Risk, Change & Stakeholder Management<\/strong>\n <p>AI agent delivery comes with moving parts - you own visibility and control.<\/p>\n <p>You will:<\/p>\n <ul>\n <li>Maintain a risk & issues log covering:<\/li>\n <ul>\n <li>Technical risks (data access, integrations, latency, environments)<\/li>\n <li>Business risks (scope creep, stakeholder shifts, external dependencies)<\/li>\n <\/ul>\n <li>Manage change transparently:<\/li>\n <ul>\n <li>Assess impact on scope, timelines, and delivery<\/li>\n <li>Align with stakeholders before execution<\/li>\n <\/ul>\n <li>Provide clear, consistent communication:<\/li>\n <ul>\n <li>Status updates<\/li>\n <li>Escalations when needed<\/li>\n <li>Expectation management throughout the lifecycle<\/li>\n <\/ul>\n <\/ul>\n <\/li>\n <li><strong>UAT, Go-Live & Post-Go-Live Stabilization<\/strong>\n <p>Plan and coordinate:<\/p>\n <ul>\n <li>UAT cycles and acceptance criteria<\/li>\n <li>Go-live readiness and rollout plans<\/li>\n <\/ul>\n <p>Ensure smooth transition:<\/p>\n <ul>\n <li>Monitor early performance and issues<\/li>\n <li>Coordinate fixes and optimizations<\/li>\n <\/ul>\n <p>Own final handover:<\/p>\n <ul>\n <li>Documentation<\/li>\n <li>Support transition<\/li>\n <li>Clear ownership post-delivery<\/li>\n <\/ul>\n <\/li>\n<\/ol>\n<h4>Requirements<\/h4>\n<ul>\n <li>5-8 years in:\n <ul>\n <li>SaaS implementation<\/li>\n <li>Technical project management<\/li>\n <li>Digital or platform delivery<\/li>\n <\/ul>\n <\/li>\n <li>3+ years delivering enterprise projects with multiple stakeholders (business & IT)<\/li>\n <li>Proven experience with:\n <ul>\n <li>Integrations, APIs, and data-driven workflows<\/li>\n <li>Background in CX, contact centers, CRM, or customer-facing platforms is a strong plus<\/li>\n <li>Experience working closely with product and engineering teams in Agile\/Scrum environments<\/li>\n <\/ul>\n <\/li>\n<\/ul>\n<h4>Must-Have Skills<\/h4>\n<ul>\n <li><strong>Project & Delivery Excellence<\/strong>\n <ul>\n <li>Strong command of:\n <ul>\n <li>Scoping, timelines, milestones<\/li>\n <li>RAID (Risks, Assumptions, Issues, Dependencies)<\/li>\n <\/ul>\n <\/li>\n <li>Confident running:\n <ul>\n <li>Standups, execution reviews, steering meetings<\/li>\n <\/ul>\n <\/li>\n <\/ul>\n <\/li>\n <li><strong>Technical Literacy (Non-Coding)<\/strong>\n <ul>\n <li>Comfortable with:\n <ul>\n <li>API-based integrations and webhooks<\/li>\n <li>Data flows between systems<\/li>\n <\/ul>\n <\/li>\n <li>Able to:\n <ul>\n <li>Read basic API documentation and JSON payloads<\/li>\n <li>Translate technical constraints into delivery decisions<\/li>\n <\/ul>\n <\/li>\n <li>Solid conceptual understanding of:\n <ul>\n <li>SaaS platforms<\/li>\n <li>LLMs and AI agent workflows<\/li>\n <\/ul>\n <\/li>\n <\/ul>\n <\/li>\n <li><strong>Stakeholder Management & Communication<\/strong>\n <ul>\n <li>Can confidently manage:\n <ul>\n <li>CX leadership<\/li>\n <li>IT and engineering teams<\/li>\n <li>Internal product and AI stakeholders<\/li>\n <\/ul>\n <\/li>\n <li>Produces:\n <ul>\n <li>Clear documentation<\/li>\n <li>Actionable recaps<\/li>\n <li>Concise, honest status updates<\/li>\n <\/ul>\n <\/li>\n <\/ul>\n <\/li>\n <li><strong>Execution Mindset<\/strong>\n <ul>\n <li>Turns ideas into:\n <ul>\n <li>Tasks, owners, and deadlines<\/li>\n <\/ul>\n <\/li>\n <li>Keeps delivery tools always current and reliable<\/li>\n <li>Strong sense of ownership and follow-through<\/li>\n <\/ul>\n <\/li>\n <li><strong>AI Project Awareness<\/strong>\n <ul>\n <li>Comfortable with:\n <ul>\n <li>Iterative AI delivery (experiments, versions, evaluation cycles)<\/li>\n <li>Data privacy, guardrails, and quality metrics<\/li>\n <\/ul>\n <\/li>\n <li>Understands that AI delivery is adaptive, not linear<\/li>\n <\/ul>\n <\/li>\n<\/ul>\n<h4>Why Join Lucidya\u2019s AI Agents Team<\/h4>\n<ul>\n <li>Work at the intersection of AI, CX, and enterprise delivery<\/li>\n <li>Shape how AI agents are deployed in real-world, high-impact environments<\/li>\n <li>Partner with strong product, AI, and engineering teams<\/li>\n <li>Own delivery end-to-end - not just coordination<\/li>\n <li>Help define delivery standards for a brand-new AI business line<\/li>\n<\/ul>\n<p>Apply now and help us redefine the future of customer experience with AI agents.<\/p><\/p><p><\/p>

<p><h4>About Lucidya<\/h4>\n<p>Lucidya is building the next generation of AI-powered customer experience solutions for enterprises across the MENA region. Our new AI Agents business line focuses on deploying intelligent, enterprise-grade AI agents that automate, assist, and augment customer-facing and operational workflows - securely, reliably, and at scale.<\/p>\n<p>This role sits at the heart of turning AI agent concepts into live, business-impacting solutions.<\/p>\n<h4>About the Role<\/h4>\n<p>The Project \/ Delivery Manager owns one critical question:<\/p>\n<p><strong>\"How do we execute what we promised?\"<\/strong><\/p>\n<p>You take the Solution Consultant\u2019s vision and turn it into a clear execution plan, structured backlog, and predictable delivery rhythm - from initial scoping through go-live and stabilization.<\/p>\n<p>You are the operational backbone of AI agent pilots and enterprise deployments, ensuring alignment across clients, engineering, data, and AI teams while keeping delivery on track.<\/p>\n<h4>Key Responsibilities<\/h4>\n<ol>\n <li><strong>Scoping & Handover from Solution Consultant<\/strong>\n <p>You step in once a pilot or project is conceptually approved.<\/p>\n <p><strong>Formal Handover<\/strong><\/p>\n <p>Receive full delivery context, including:<\/p>\n <ul>\n <li>Discovery findings<\/li>\n <li>Workflow maps and agent logic<\/li>\n <li>Success criteria and KPIs<\/li>\n <li>Pilot narrative and client expectations<\/li>\n <\/ul>\n <p>Clarify:<\/p>\n <ul>\n <li>Scope, constraints, dependencies, and assumptions<\/li>\n <li>Technical and operational boundaries<\/li>\n <\/ul>\n <p><strong>Scope Confirmation<\/strong><\/p>\n <p>Translate high-level workflows into clear delivery components:<\/p>\n <ul>\n <li>AI Agent versions (v0, v1, v2\u2026)<\/li>\n <li>Integrations, channels, and data sources<\/li>\n <li>Dashboards, reporting, and monitoring<\/li>\n <li>Training, enablement, and documentation<\/li>\n <\/ul>\n <p>Align internally and with the client on:<\/p>\n <ul>\n <li>What is in scope vs out of scope for each phase<\/li>\n <\/ul>\n <\/li>\n <li><strong>Detailed Planning & Backlog Management<\/strong>\n <p>This is where ideas become execution.<\/p>\n <p>You own:<\/p>\n <ul>\n <li><strong>Building the delivery plan and timeline:<\/strong><\/li>\n <ul>\n <li>Milestones, sprints, and go-live checkpoints<\/li>\n <li>Cross-team dependencies (AI, backend, integrations, data, CX ops)<\/li>\n <\/ul>\n <li><strong>Creating and maintaining the delivery backlog:<\/strong><\/li>\n <ul>\n <li>Break down deliverables into tasks and subtasks<\/li>\n <li>Assign clear owners (AI Agent Engineers, Backend, Frontend, Data, Solutions)<\/li>\n <\/ul>\n <li><strong>Keeping tools accurate and trusted:<\/strong><\/li>\n <ul>\n <li>Trello \/ Jira \/ Notion as the single source of truth<\/li>\n <li>Task status, blockers, due dates, and changes<\/li>\n <\/ul>\n <\/ul>\n <\/li>\n <li><strong>Coordination & Day-to-Day Execution<\/strong>\n <p>You are the operational heartbeat of each pilot or project.<\/p>\n <p>Responsibilities include:<\/p>\n <ul>\n <li>Running regular execution cadences:<\/li>\n <ul>\n <li>Standups and check-ins<\/li>\n <li>Progress reviews and decision syncs<\/li>\n <\/ul>\n <li>Ensuring tight collaboration between:<\/li>\n <ul>\n <li>Solution Consultants (business & workflows)<\/li>\n <li>Engineering and AI teams (implementation)<\/li>\n <li>Client stakeholders (CX, IT, Operations, Compliance)<\/li>\n <\/ul>\n <li>Driving execution discipline:<\/li>\n <ul>\n <li>Clear meeting notes<\/li>\n <li>Action items with owners and deadlines<\/li>\n <li>Relentless follow-up until closure<\/li>\n <\/ul>\n <\/ul>\n <\/li>\n <li><strong>Risk, Change & Stakeholder Management<\/strong>\n <p>AI agent delivery comes with moving parts - you own visibility and control.<\/p>\n <p>You will:<\/p>\n <ul>\n <li>Maintain a risk & issues log covering:<\/li>\n <ul>\n <li>Technical risks (data access, integrations, latency, environments)<\/li>\n <li>Business risks (scope creep, stakeholder shifts, external dependencies)<\/li>\n <\/ul>\n <li>Manage change transparently:<\/li>\n <ul>\n <li>Assess impact on scope, timelines, and delivery<\/li>\n <li>Align with stakeholders before execution<\/li>\n <\/ul>\n <li>Provide clear, consistent communication:<\/li>\n <ul>\n <li>Status updates<\/li>\n <li>Escalations when needed<\/li>\n <li>Expectation management throughout the lifecycle<\/li>\n <\/ul>\n <\/ul>\n <\/li>\n <li><strong>UAT, Go-Live & Post-Go-Live Stabilization<\/strong>\n <p>Plan and coordinate:<\/p>\n <ul>\n <li>UAT cycles and acceptance criteria<\/li>\n <li>Go-live readiness and rollout plans<\/li>\n <\/ul>\n <p>Ensure smooth transition:<\/p>\n <ul>\n <li>Monitor early performance and issues<\/li>\n <li>Coordinate fixes and optimizations<\/li>\n <\/ul>\n <p>Own final handover:<\/p>\n <ul>\n <li>Documentation<\/li>\n <li>Support transition<\/li>\n <li>Clear ownership post-delivery<\/li>\n <\/ul>\n <\/li>\n<\/ol>\n<h4>Requirements<\/h4>\n<ul>\n <li>5-8 years in:\n <ul>\n <li>SaaS implementation<\/li>\n <li>Technical project management<\/li>\n <li>Digital or platform delivery<\/li>\n <\/ul>\n <\/li>\n <li>3+ years delivering enterprise projects with multiple stakeholders (business & IT)<\/li>\n <li>Proven experience with:\n <ul>\n <li>Integrations, APIs, and data-driven workflows<\/li>\n <li>Background in CX, contact centers, CRM, or customer-facing platforms is a strong plus<\/li>\n <li>Experience working closely with product and engineering teams in Agile\/Scrum environments<\/li>\n <\/ul>\n <\/li>\n<\/ul>\n<h4>Must-Have Skills<\/h4>\n<ul>\n <li><strong>Project & Delivery Excellence<\/strong>\n <ul>\n <li>Strong command of:\n <ul>\n <li>Scoping, timelines, milestones<\/li>\n <li>RAID (Risks, Assumptions, Issues, Dependencies)<\/li>\n <\/ul>\n <\/li>\n <li>Confident running:\n <ul>\n <li>Standups, execution reviews, steering meetings<\/li>\n <\/ul>\n <\/li>\n <\/ul>\n <\/li>\n <li><strong>Technical Literacy (Non-Coding)<\/strong>\n <ul>\n <li>Comfortable with:\n <ul>\n <li>API-based integrations and webhooks<\/li>\n <li>Data flows between systems<\/li>\n <\/ul>\n <\/li>\n <li>Able to:\n <ul>\n <li>Read basic API documentation and JSON payloads<\/li>\n <li>Translate technical constraints into delivery decisions<\/li>\n <\/ul>\n <\/li>\n <li>Solid conceptual understanding of:\n <ul>\n <li>SaaS platforms<\/li>\n <li>LLMs and AI agent workflows<\/li>\n <\/ul>\n <\/li>\n <\/ul>\n <\/li>\n <li><strong>Stakeholder Management & Communication<\/strong>\n <ul>\n <li>Can confidently manage:\n <ul>\n <li>CX leadership<\/li>\n <li>IT and engineering teams<\/li>\n <li>Internal product and AI stakeholders<\/li>\n <\/ul>\n <\/li>\n <li>Produces:\n <ul>\n <li>Clear documentation<\/li>\n <li>Actionable recaps<\/li>\n <li>Concise, honest status updates<\/li>\n <\/ul>\n <\/li>\n <\/ul>\n <\/li>\n <li><strong>Execution Mindset<\/strong>\n <ul>\n <li>Turns ideas into:\n <ul>\n <li>Tasks, owners, and deadlines<\/li>\n <\/ul>\n <\/li>\n <li>Keeps delivery tools always current and reliable<\/li>\n <li>Strong sense of ownership and follow-through<\/li>\n <\/ul>\n <\/li>\n <li><strong>AI Project Awareness<\/strong>\n <ul>\n <li>Comfortable with:\n <ul>\n <li>Iterative AI delivery (experiments, versions, evaluation cycles)<\/li>\n <li>Data privacy, guardrails, and quality metrics<\/li>\n <\/ul>\n <\/li>\n <li>Understands that AI delivery is adaptive, not linear<\/li>\n <\/ul>\n <\/li>\n<\/ul>\n<h4>Why Join Lucidya\u2019s AI Agents Team<\/h4>\n<ul>\n <li>Work at the intersection of AI, CX, and enterprise delivery<\/li>\n <li>Shape how AI agents are deployed in real-world, high-impact environments<\/li>\n <li>Partner with strong product, AI, and engineering teams<\/li>\n <li>Own delivery end-to-end - not just coordination<\/li>\n <li>Help define delivery standards for a brand-new AI business line<\/li>\n<\/ul>\n<p>Apply now and help us redefine the future of customer experience with AI agents.<\/p><\/p><p><\/p>

<p><h4>Key responsibilities</h4> <p>Design, implement, and continuously improve a comprehensive project and program governance framework aligned with the bank's strategic objectives, incorporating governance policies, procedures, methodologies, templates, and standards based on industry best practices.<br> Assess the current project management operating model, identify process improvement opportunities, and lead initiatives that enhance operational efficiency, service quality, and project delivery effectiveness.<br> Define governance procedures for projects and programs across the group, establish RACI matrices for all key project deliverables, monitor compliance, and provide guidance and support to project stakeholders.<br> Develop project and program quality standards across the bank, conduct periodic governance compliance reviews for projects managed by both the enterprise PMO and other business units, report findings to the head of enterprise PMO, and recommend improvement initiatives.<br> Review, challenge, validate, and consolidate project reports submitted by project managers while standardizing reporting formats and executive presentations for senior management.<br> Establish and monitor key performance indicators (KPIs) to measure project and program performance, governance effectiveness, and resource utilization. Analyze performance variances, recommend corrective actions, and provide regular management reports.<br> Ensure governance policies, procedures, templates, and methodologies comply with regulatory requirements. Identify project risks, establish appropriate governance controls, and implement risk mitigation measures throughout the project lifecycle.<br> Participate in the evaluation, selection, implementation, and enhancement of project management and reporting tools. Coordinate with relevant stakeholders to deliver awareness sessions and training that ensure standardized reporting and consistent project performance measurement.<br> Promote governance awareness and provide training to project and program managers across the bank to strengthen governance capabilities and standardize project management practices.<br> Serve as the primary liaison between the enterprise PMO and other business units, supporting requests from internal audit, finance, and other corporate functions.<br> Review executive reports, regulatory reports, and internal and external audit findings, ensure timely implementation of corrective actions, and prevent recurrence through sustainable process improvements.<br> Participate as a primary or alternate member of the bank's business continuity management (BCM) and emergency response teams, carrying out assigned responsibilities to support operational resilience and business recovery.</p> <h4>Requirements</h4> <p>Bachelor's degree in engineering, computer science, management information systems (MIS), or a related discipline.<br> Minimum of 10 years of experience in project management and project governance, preferably within the banking or financial services sector.<br> Strong knowledge of project governance frameworks and project management methodologies.<br> Excellent analytical and problem-solving skills.<br> Process improvement and continuous improvement mindset.<br> Strong planning, organization, and prioritization skills.<br> Leadership and stakeholder management capabilities.<br> Excellent written and verbal communication skills in both Arabic and English.<br> Advanced reporting and presentation skills.<br> Proficiency in project management and business systems.<br> Strong understanding of internal policies, procedures, and applicable regulatory requirements.<br> Ability to work collaboratively in cross-functional teams.<br> Ability to perform effectively under pressure in a fast-paced environment.</p> <h4>Professional certifications</h4> <p>One or more of the following certifications is preferred:<br> Project Management Professional (PMP)<br> PMO-related professional certifications<br> Lean Six Sigma</p></p><p></p>

<p><h4>Key responsibilities</h4> <p>Design, implement, and continuously improve a comprehensive project and program governance framework aligned with the bank's strategic objectives, incorporating governance policies, procedures, methodologies, templates, and standards based on industry best practices.<br> Assess the current project management operating model, identify process improvement opportunities, and lead initiatives that enhance operational efficiency, service quality, and project delivery effectiveness.<br> Define governance procedures for projects and programs across the group, establish RACI matrices for all key project deliverables, monitor compliance, and provide guidance and support to project stakeholders.<br> Develop project and program quality standards across the bank, conduct periodic governance compliance reviews for projects managed by both the enterprise PMO and other business units, report findings to the head of enterprise PMO, and recommend improvement initiatives.<br> Review, challenge, validate, and consolidate project reports submitted by project managers while standardizing reporting formats and executive presentations for senior management.<br> Establish and monitor key performance indicators (KPIs) to measure project and program performance, governance effectiveness, and resource utilization. Analyze performance variances, recommend corrective actions, and provide regular management reports.<br> Ensure governance policies, procedures, templates, and methodologies comply with regulatory requirements. Identify project risks, establish appropriate governance controls, and implement risk mitigation measures throughout the project lifecycle.<br> Participate in the evaluation, selection, implementation, and enhancement of project management and reporting tools. Coordinate with relevant stakeholders to deliver awareness sessions and training that ensure standardized reporting and consistent project performance measurement.<br> Promote governance awareness and provide training to project and program managers across the bank to strengthen governance capabilities and standardize project management practices.<br> Serve as the primary liaison between the enterprise PMO and other business units, supporting requests from internal audit, finance, and other corporate functions.<br> Review executive reports, regulatory reports, and internal and external audit findings, ensure timely implementation of corrective actions, and prevent recurrence through sustainable process improvements.<br> Participate as a primary or alternate member of the bank's business continuity management (BCM) and emergency response teams, carrying out assigned responsibilities to support operational resilience and business recovery.</p> <h4>Requirements</h4> <p>Bachelor's degree in engineering, computer science, management information systems (MIS), or a related discipline.<br> Minimum of 10 years of experience in project management and project governance, preferably within the banking or financial services sector.<br> Strong knowledge of project governance frameworks and project management methodologies.<br> Excellent analytical and problem-solving skills.<br> Process improvement and continuous improvement mindset.<br> Strong planning, organization, and prioritization skills.<br> Leadership and stakeholder management capabilities.<br> Excellent written and verbal communication skills in both Arabic and English.<br> Advanced reporting and presentation skills.<br> Proficiency in project management and business systems.<br> Strong understanding of internal policies, procedures, and applicable regulatory requirements.<br> Ability to work collaboratively in cross-functional teams.<br> Ability to perform effectively under pressure in a fast-paced environment.</p> <h4>Professional certifications</h4> <p>One or more of the following certifications is preferred:<br> Project Management Professional (PMP)<br> PMO-related professional certifications<br> Lean Six Sigma</p></p><p></p>

<p><h4>Description</h4> <p>Mindrift is looking for highly skilled senior Python data scraping engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.</p> <p>In this role, as an AI pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.</p> <p>This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction, and processing.</p> <h4>What we do</h4> <p>The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of generative AI by tapping into real-world expertise from across the globe.</p> <p>This is a freelance role for a Tendem project. As a senior Python data scraping engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.</p> <h4>Key responsibilities:</h4> <ul> <li>Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.</li> <li>Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.</li> <li>Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.</li> <li>Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.</li> <li>Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.</li> </ul> <h4>Requirements:</h4> <ul> <li>At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).</li> <li>Bachelor’s or master’s degree in engineering, applied mathematics, computer science, or related technical fields is a plus.</li> <li>Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows. We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.</li> <li>Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.</li> <li>Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).</li> <li>Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).</li> <li>Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale.</li> <li>Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows.</li> <li>Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks.</li> <li>Strong attention to detail and commitment to data accuracy.</li> <li>Self-directed work ethic with ability to troubleshoot independently.</li> <li>English proficiency: upper-intermediate (B2) or above (required).</li> </ul> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $25 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Description</h4> <p>Mindrift is looking for highly skilled senior Python data scraping engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.</p> <p>In this role, as an AI pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.</p> <p>This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction, and processing.</p> <h4>What we do</h4> <p>The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of generative AI by tapping into real-world expertise from across the globe.</p> <p>This is a freelance role for a Tendem project. As a senior Python data scraping engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.</p> <h4>Key responsibilities:</h4> <li>Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.</li> <li>Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.</li> <li>Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.</li> <li>Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.</li> <li>Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.</li> <h4>Requirements:</h4> <li>Five or more years of relevant experience in data engineering, web scraping, automation, or software development (required).</li> <li>Bachelor’s or master’s degree in engineering, applied mathematics, computer science, or related technical fields is a plus.</li> <li>Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows. We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.</li> <li>Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.</li> <li>Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).</li> <li>Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).</li> <li>Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale.</li> <li>Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows.</li> <li>Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks.</li> <li>Strong attention to detail and commitment to data accuracy.</li> <li>Self-directed work ethic with ability to troubleshoot independently.</li> <li>English proficiency: upper-intermediate (B2) or above (required).</li> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $25 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Mindrift is looking for highly skilled senior python data scraping engineers to join the tendem project and drive specialized data scraping workflows within our hybrid AI + human system.</h4> <p>In this role, as an AI Pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.</p> <p>This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.</p> <h4>What we do</h4> <p>The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of generative AI by tapping into real-world expertise from across the globe.</p> <p>This is a freelance role for a Tendem project. As a senior python data scraping engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.</p> <h4>Key responsibilities:</h4> <li>Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.</li> <li>Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.</li> <li>Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle javascript-rendered content and changing site behavior.</li> <li>Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.</li> <li>Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.</li> <h4>Requirements:</h4> <li>At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).</li> <li>Bachelor’s or master’s degree in engineering, applied mathematics, computer science, or related technical fields is a plus.</li> <li>Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows. We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.</li> <li>Strong experience in python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.</li> <li>Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).</li> <li>Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).</li> <li>Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale.</li> <li>Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows.</li> <li>Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks.</li> <li>Strong attention to detail and commitment to data accuracy.</li> <li>Self-directed work ethic with ability to troubleshoot independently.</li> <li>A link to GitHub is a plus.</li> <li>English proficiency: upper-intermediate (B2) or above (required).</li> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $25 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Role overview</h4> <p>We are seeking a highly skilled senior AI infrastructure and platform engineer to join our client’s team in Riyadh. In this role, you’ll be responsible for building, managing, and optimizing scalable AI infrastructure and compute environments that support high-performance workloads, including GPU-accelerated AI/ML pipelines, cluster scheduling, and orchestration.</p> <h4>Key responsibilities</h4> <ul> <li>Deploy, maintain, and optimize GPU-based compute clusters and infrastructure.</li> <li>Manage and operate GPU orchestration tools and platforms such as: <ul> <li>Nvidia Base Command Manager (critical)</li> <li>Nvidia AI Enterprise Suite</li> <li>Nvidia GPU and Network Operators</li> <li>Nvidia NIMs and Blueprints</li> </ul> </li> <li>Configure, deploy, and maintain compute workloads using scheduling and orchestration tools including: <ul> <li>Slurm (critical)</li> <li>Vanilla Kubernetes</li> </ul> </li> <li>Install, configure, and maintain the underlying OS (e.g. Canonical Ubuntu) and supporting system software.</li> <li>Monitor and troubleshoot infrastructure performance, availability, and reliability; ensure high uptime for AI/ML workloads.</li> <li>Work with data scientists, ML engineers, and development teams to define infrastructure requirements, resource allocation, and deployment workflows.</li> <li>Develop automation scripts, CI/CD pipelines, and best practices for infrastructure provisioning and management.</li> <li>Document architecture, configurations, and operational procedures; enforce security, compliance, and backup policies.</li> </ul> <h4>Requirements</h4> <h5>Required skills & experience</h5> <ul> <li>Proven experience managing GPU-based AI/ML infrastructure and compute clusters.</li> <li>Hands-on experience with: <ul> <li>Nvidia Base Command Manager</li> <li>Nvidia AI Enterprise Suite</li> <li>Nvidia GPU/Network Operators, NIMs, Blueprints</li> </ul> </li> <li>Strong experience with Slurm and/or Kubernetes orchestration.</li> <li>Solid Linux system administration skills — preferably on Ubuntu or similar distributions.</li> <li>Strong scripting/automation ability (e.g. Bash, Python, or relevant tooling) for provisioning, deployment, and maintenance.</li> <li>Excellent troubleshooting and performance-tuning skills.</li> <li>Experience collaborating with ML/data science teams and integrating infrastructure with their workflows.</li> <li>Strong understanding of networking, security, resource allocation, and cluster management best practices.</li> </ul> <h5>Preferred qualifications</h5> <ul> <li>Previous experience working in a high-performance computing (HPC) or AI-focused infrastructure team.</li> <li>Knowledge of containerization, container orchestration, and GPUs in cloud or on-prem environments.</li> <li>Experience with CI/CD, infrastructure-as-code (e.g. Terraform, Ansible), monitoring tools, and logging setups.</li> <li>Familiarity with workload scheduling, job queuing, resource quotas, and GPU-shared environments.</li> </ul></p><p></p>

<p>We are seeking an experienced Technical Architect to lead the design and implementation of technology solutions that support business objectives and align with enterprise architecture standards. The ideal candidate will combine strong technical expertise with strategic thinking to deliver scalable, secure, and high-performing solutions while providing technical leadership across projects. Key Responsibilities Design end-to-end technical architectures for enterprise systems, applications, and integrations. Develop architecture blueprints, technical specifications, and solution design documentation. Evaluate, recommend, and select appropriate technologies, frameworks, platforms, and tools based on business and technical requirements. Provide technical leadership and guidance to development teams throughout the software development lifecycle. Ensure solutions are scalable, secure, maintainable, and aligned with industry best practices and organizational standards. Conduct architecture and code reviews to ensure compliance with technical standards and quality requirements. Collaborate with business analysts, project managers, product owners, and key stakeholders to translate business requirements into effective technical solutions. Identify technical risks, dependencies, and constraints, and develop mitigation strategies. Design and oversee system integration approaches to ensure seamless interoperability between applications and platforms. Stay up to date with emerging technologies, industry trends, and architectural best practices to drive innovation. Mentor and support junior architects, developers, and technical team members by promoting knowledge sharing and continuous improvement.</p><p><strong>Desired Candidate Profile</strong></p><p>Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field. Proven experience in solution or technical architecture, software design, and enterprise application development. Strong understanding of cloud platforms, system integration, APIs, microservices, and enterprise architecture principles. Experience with modern development frameworks, databases, and DevOps practices. Excellent analytical, problem-solving, and communication skills. Ability to collaborate effectively with cross-functional teams and influence technical decisions. Relevant architecture or cloud certifications are considered an advantage.</p>

Job Purpose<p></p> <div> <p>The Senior PreSales Engineer IT Infrastructure Systems is responsible for end-to-end technical solutioning across enterprise compute, storage, hyperconverged infrastructure (HCI), virtualization, backup, disaster recovery, and hybrid cloud integration.</p></div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>About the Role</p><p>EY's AI Hub is looking for an experienced Automation QA Engineer to ensure the quality, reliability, and performance of our applications, including AI-powered products built on modern web stacks. You'll design and maintain automated test suites for applications built with Next.js and Python, with a strong focus on cross-browser testing and CI/CD integration.</p><p>What You'll Do</p><ul><li>Design, build, and maintain automated test frameworks and suites for web applications (Next.js frontend, Python backend/services)</li><li>Develop and execute cross-browser automated test scripts to ensure consistent functionality across Chrome, Firefox, Safari, and Edge</li><li>Integrate automated tests into CI/CD pipelines (Jenkins, GitHub Actions, or similar) to enable continuous testing and fast feedback loops</li><li>Collaborate with developers, product managers, and other QA engineers to define test strategies and acceptance criteria</li><li>Identify, document, and track bugs through to resolution, working closely with engineering teams</li><li>Perform functional, regression, integration, and end-to-end testing</li><li>Continuously improve test coverage, automation efficiency, and overall QA processes</li><li>Contribute to test planning for AI-driven features and help define quality benchmarks for AI model outputs where applicable</li><li>Monitor and maintain test environments and test data</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>4 – 8 years of experience in automation QA / SDET roles</li><li>Strong hands-on experience testing web applications, ideally with Next.js/React-based frontends</li><li>Proficiency in Python for writing test automation scripts and frameworks</li><li>Solid experience with cross-browser testing tools and strategies</li><li>Experience integrating automated tests into CI/CD pipelines (Jenkins, GitHub Actions, or similar)</li><li>Strong understanding of QA methodologies: functional, regression, integration, and end-to-end testing</li><li>Familiarity with version control systems (Git)</li><li>Strong analytical and debugging skills, with attention to detail</li><li>Good communication skills and ability to work closely with cross-functional teams</li><li>Nice to Have: Experience working on AI/ML-powered projects or products (e.g., testing AI model outputs, chatbots, LLM-based features)</li><li>Familiarity with API testing tools (Postman, REST Assured, etc.)</li><li>Experience with performance or load testing</li><li>Exposure to cloud platforms (AWS, Azure, or GCP)</li></ul><p></p></section>

<p><h4>Description</h4> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.</p> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Design original computational engineering problems that simulate real engineering workflows;</li> <li>Create problems requiring Python programming to solve engineering calculations and simulations;</li> <li>Ensure problems are computationally intensive and require numerical methods or iterative solutions;</li> <li>Develop problems involving system design, optimization, and analysis;</li> <li>Base problems on real research challenges or practical applications from engineering practice;</li> <li>Verify solutions using Python with standard engineering libraries;</li> <li>Document problem statements clearly and provide verified correct answers.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for engineers with experience in Python open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Mechanical Engineering or related fields;</li> <li>Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata, or knowledge of any programming language can be equivalent;</li> <li>2+ years of professional experience: applied, research, or teaching experience is applicable;</li> <li>Understanding of practical engineering constraints and approximations;</li> <li>Strong written English (C1+);</li> <li>Professional certifications (e.g., CMME, SAS Certifications, CAP) and experience in international or applied projects are an advantage.</li> </ul> <h4>How it works</h4> <p>Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $37 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Description</h4> <p>Are you ready to take the lead in driving technical excellence? Optimiza is looking for a dynamic and engaging technical team leader to inspire and guide our talented team of engineers and developers. As the technical team leader, you will play a pivotal role in shaping project success, fostering collaboration, and delivering cutting-edge solutions that exceed client expectations.</p> <h4>Key responsibilities:</h4> <ul> <li>Lead, mentor, and motivate a team of technical professionals to achieve project goals with a passion for quality and innovation.</li> <li>Plan, coordinate, and oversee technical project deliverables while ensuring timely and successful completion.</li> <li>Collaborate closely with stakeholders, project managers, and cross-functional teams to align technical efforts with business objectives.</li> <li>Drive continuous improvement by encouraging knowledge sharing, adopting best practices, and promoting a culture of learning.</li> <li>Identify risks and challenges early and implement effective solutions to keep projects on track.</li> <li>Communicate complex technical concepts clearly and engagingly to both technical team members and non-technical stakeholders.</li> <li>Stay ahead of the curve by keeping up with the latest technology trends and integrating relevant advancements into team practices.</li> </ul> <h4>Requirements</h4> <ul> <li>Bachelor's degree in computer science, engineering, or related field.</li> <li>Years of experience: 6+ years</li> <li>Technical knowledge: system administration, good knowledge in Windows, Linux, and networking (infrastructure support background)</li> <li>Good troubleshooting skills including networking and system administration.</li> <li>Customer support job experience.</li> </ul> <h4>Preferred skills</h4> <ul> <li>API traffic flow knowledge</li> <li>Database</li> <li>Active Directory and group policy</li> </ul> <h4>Benefits</h4> <ul> <li>Annual bonus</li> <li>Class A health insurance</li> <li>Training and development</li> <li>Performance bonus</li> </ul></p><p></p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n<li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n<li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n<li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n<li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n<li>Not data labeling<\/li>\n<li>Not prompt engineering<\/li>\n<li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n<li>5+ years in software development<\/li>\n<li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n<li>Experience writing tests (functional, integration)<\/li>\n<li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply ? Pass qualification(s) ? Join a project ? Complete tasks ? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description</h4> <p>A leading global pharmaceutical company is seeking an AI solutions architect who is responsible for designing, governing, delivering, and evolving the enterprise AI technical architecture across the company. Acting as the technical authority and delivery lead for AI within the AI Centre of Excellence, this role defines architectural standards, evaluates and governs AI platforms and solutions, prioritising off-the-shelf and vendor-led approaches, and ensures that all AI initiatives are scalable, secure, compliant, and aligned with the company's digital transformation strategy. The AI solutions architect works closely with AI engineers, IT business partners, AI champions, and business function leaders to assess technical feasibility, lead end-to-end solution delivery, support AI proof of value (POV) execution, and translate strategic AI ambitions into sound, future-proof solutions, ensuring every initiative is delivered on a technically rigorous and governance-compliant foundation.</p> <h4>Responsibilities:</h4> <ol> <li><strong>Strategy & architecture leadership</strong><br> Define and own the enterprise AI technical architecture framework, including reference architectures, design patterns, integration blueprints, and technology standards across cloud and on-premises environments.<br> Collaborate with the architecture advisory board to ensure the AI architecture roadmap is aligned with the company's overall digital transformation strategy and enterprise IT architecture principles.<br> Evaluate emerging AI technologies, frameworks, and platforms, providing technical direction and recommendations to senior IT and business stakeholders.<br> Lead architectural governance for all AI initiatives, ensuring solutions adhere to approved standards, security requirements, regulatory constraints, and scalability principles.<br> Define and maintain the enterprise AI technology stack, including cloud AI services (Azure, AWS, GCP), MLOps platforms, data platforms, and integration middleware.</li> <li><strong>AI solution design & technical oversight</strong><br> Architect end-to-end AI solutions across the company's key business domains including manufacturing, quality & regulatory affairs, R&D, commercial, supply chain, HR, and finance.<br> Produce high-quality architecture deliverables including solution design documents, architecture decision records (ADRs), technical specifications, data flow diagrams, and integration architecture blueprints.<br> Lead technical design reviews and architecture assessments for all AI initiatives in the portfolio, ensuring fitness for purpose, scalability, and compliance.<br> Define AI integration patterns with enterprise systems including SAP, MES, LIMS, CRM, and M365 ecosystems, ensuring seamless interoperability.<br> Guide AI developers in translating architecture designs into well-structured, maintainable, and production-ready solutions.<br> Oversee the design of MLOps pipelines including model training, validation, deployment, monitoring, and retraining workflows.</li> <li><strong>Platform engineering & infrastructure</strong><br> Own the architecture and governance of enterprise AI platforms including Microsoft Azure AI, Azure Machine Learning, Microsoft 365 Copilot, and other approved AI tooling.<br> Define cloud infrastructure architecture for AI workloads including compute, storage, networking, and security configurations aligned with the company IT standards.<br> Establish standards for model lifecycle management including versioning, registry, performance monitoring, drift detection, and retraining triggers.<br> Drive the design of data architecture components critical to AI including feature stores, data lakes, vector databases, and real-time data pipelines in collaboration with the Data & Analytics team.<br> Ensure AI platforms meet GxP validation, 21 CFR Part 11, and audit trail requirements where applicable.</li> <li><strong>Governance, compliance & responsible AI</strong><br> Embed regulatory and compliance requirements, including FDA AI/ML guidance, EMA requirements, GxP, GDPR, and HIPAA, into AI architecture design and review processes.<br> Define and enforce responsible AI architectural guardrails including model explainability, bias detection, fairness assessments, and human-in-the-loop design patterns.<br> Maintain AI architecture governance documentation including standards, patterns, approved toolsets, and deviation processes within the enterprise AI knowledge repository.<br> Coordinate with IT security, data privacy, legal, quality assurance, and regulatory affairs to ensure AI solutions meet all applicable oversight requirements.<br> Support E-AIAB governance processes by providing technical input into initiative assessments, vendor evaluations, and POV planning.</li> <li><strong>Technical leadership & enablement</strong><br> Provide technical mentorship, code and architecture reviews, and hands-on guidance to the AI developer team.<br> Define engineering best practices, coding standards, and DevOps/MLOps conventions for the AI team.<br> Collaborate with external vendors, implementation partners, and cloud providers to assess solutions, conduct technical due diligence, and ensure delivery quality.<br> Contribute technical expertise to vendor RFP/RFI processes, proof-of-concept evaluations, and contract assessments.<br> Represent the company's AI technical standards in cross-functional project delivery teams and steering committees.</li> <li><strong>Stakeholder engagement & communication</strong><br> Translate complex technical architecture concepts into clear, accessible language for business stakeholders, executive leadership, and non-technical audiences.<br> Serve as the primary technical escalation point for AI platform issues, architecture deviations, and integration challenges.<br> Collaborate with IT business partners and AI champions to provide technical feasibility input into AI opportunity assessments.<br> Participate in external pharmaceutical AI forums, cloud provider events, and technology conferences to maintain leading-edge awareness and contribute to the company's technical reputation.</li> </ol> <h4>Requirements</h4> <p>Bachelor's degree in computer science, information technology, software engineering, data science, or related technical field.<br> Master's degree in artificial intelligence, data science, computer science, or related discipline is preferred.<br> Microsoft Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent cloud architecture certification is preferred.<br> TOGAF or equivalent enterprise architecture certification is preferred.<br> 7–10 years of professional experience in IT, software engineering, data & analytics, or AI/ML implementation.<br> 4–6 years of hands-on experience designing and delivering AI/ML solutions on cloud platforms (Azure, AWS, or GCP) in a production environment.<br> Proven track record of owning end-to-end AI solution architecture in a complex, cross-functional enterprise environment.<br> Experience with Microsoft Azure AI, Azure Machine Learning, and Microsoft 365 Copilot architecture and deployment is preferred.<br> Pharmaceutical, healthcare, life sciences, or other regulated industry experience is preferred.<br> Experience with GxP validation, 21 CFR Part 11, or regulatory technology compliance in an AI/ML context is preferred.</p> <h4>Skills:</h4> <p><strong>Technical competencies:</strong><br> AI/ML architecture & solution design - cloud platform architecture (Azure / AWS / GCP) - ML ops & model lifecycle management - enterprise integration & API design - data architecture & data engineering - AI governance, ethics & responsible AI - pharmaceutical regulatory compliance (GxP, FDA, EMA)</p> <p><strong>AI & technology skills:</strong><br> Deep expertise in AI/ML architecture patterns, including supervised/unsupervised learning, NLP, computer vision, generative AI, and LLM-based solution design.<br> Strong hands-on proficiency with Azure AI services, Azure Machine Learning, MLflow, or equivalent MLOps tooling.<br> Solid experience designing and deploying generative AI solutions including RAG architectures, LLM orchestration (LangChain, Semantic Kernel), and enterprise copilot patterns.<br> Strong command of enterprise integration architecture including REST APIs, event-driven architecture, message queues, and middleware platforms.<br> Proficiency in cloud infrastructure design including IaC (Terraform, Bicep), containerization (Docker, Kubernetes), and CI/CD pipelines.<br> Strong understanding of data architecture components including data lakes, lakehouses, feature stores, and vector databases.<br> Working knowledge of pharmaceutical business processes including GxP operations, quality management systems, and regulatory affairs workflows (preferred).<br> Solid understanding of AI governance frameworks, responsible AI principles, data privacy regulations (GDPR, HIPAA), and IT security principles relevant to AI deployment.</p></p><p></p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n<li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n<li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n<li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n<li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n<li>Not data labeling<\/li>\n<li>Not prompt engineering<\/li>\n<li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n<li>5+ years in software development<\/li>\n<li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n<li>Experience writing tests (functional, integration)<\/li>\n<li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply ? Pass qualification(s) ? Join a project ? Complete tasks ? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at approximately 20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>A leading global pharmaceutical company is seeking an AI Solutions Architect who is responsible for designing, governing, delivering, and evolving the enterprise AI technical architecture across the company. Acting as the technical authority and delivery lead for AI within the AI Centre of Excellence, this role defines architectural standards, evaluates and governs AI platforms and solutions, prioritising off-the-shelf and vendor-led approaches, and ensures that all AI initiatives are scalable, secure, compliant, and aligned with the company's digital transformation strategy. The AI Solutions Architect works closely with AI Engineers, IT Business Partners, AI Champions, and business function leaders to assess technical feasibility, lead end-to-end solution delivery, support AI Proof of Value (POV) execution, and translate strategic AI ambitions into sound, future-proof solutions, ensuring every initiative is delivered on a technically rigorous and governance-compliant foundation.</p><p>Responsibilities:</p><ol><li>Strategy &amp; Architecture Leadership<ul><li>Define and own the enterprise AI technical architecture framework, including reference architectures, design patterns, integration blueprints, and technology standards across cloud and on-premises environments</li><li>Collaborate with the Architecture advisory board to ensure the AI architecture roadmap is aligned with the company's overall digital transformation strategy and enterprise IT architecture principles</li><li>Evaluate emerging AI technologies, frameworks, and platforms, providing technical direction and recommendations to senior IT and business stakeholders</li><li>Lead architectural governance for all AI initiatives, ensuring solutions adhere to approved standards, security requirements, regulatory constraints, and scalability principles</li><li>Define and maintain the enterprise AI technology stack, including cloud AI services (Azure, AWS, GCP), MLOps platforms, data platforms, and integration middleware</li></ul></li><li>AI Solution Design &amp; Technical Oversight<ul><li>Architect end-to-end AI solutions across the company's key business domains including Manufacturing, Quality &amp; Regulatory Affairs, R&amp;D, Commercial, Supply Chain, HR, and Finance</li><li>Produce high-quality architecture deliverables including solution design documents, architecture decision records (ADRs), technical specifications, data flow diagrams, and integration architecture blueprints</li><li>Lead technical design reviews and architecture assessments for all AI initiatives in the portfolio, ensuring fitness for purpose, scalability, and compliance</li><li>Define AI integration patterns with enterprise systems including SAP, MES, LIMS, CRM, and M365 ecosystems, ensuring seamless interoperability</li><li>Guide AI Developers in translating architecture designs into well-structured, maintainable, and production-ready solutions</li><li>Oversee the design of MLOps pipelines including model training, validation, deployment, monitoring, and retraining workflows</li></ul></li><li>Platform Engineering &amp; Infrastructure<ul><li>Own the architecture and governance of enterprise AI platforms including Microsoft Azure AI, Azure Machine Learning, Microsoft 365 Copilot, and other approved AI tooling</li><li>Define cloud infrastructure architecture for AI workloads including compute, storage, networking, and security configurations aligned with the company IT standards</li><li>Establish standards for model lifecycle management including versioning, registry, performance monitoring, drift detection, and retraining triggers</li><li>Drive the design of data architecture components critical to AI including feature stores, data lakes, vector databases, and real-time data pipelines in collaboration with the Data &amp; Analytics team</li><li>Ensure AI platforms meet GxP validation, 21 CFR Part 11, and audit trail requirements where applicable</li></ul></li><li>Governance, Compliance &amp; Responsible AI<ul><li>Embed regulatory and compliance requirements, including FDA AI/ML guidance, EMA requirements, GxP, GDPR, and HIPAA, into AI architecture design and review processes</li><li>Define and enforce responsible AI architectural guardrails including model explainability, bias detection, fairness assessments, and human-in-the-loop design patterns</li><li>Maintain AI architecture governance documentation including standards, patterns, approved toolsets, and deviation processes within the enterprise AI knowledge repository</li><li>Coordinate with IT Security, Data Privacy, Legal, Quality Assurance, and Regulatory Affairs to ensure AI solutions meet all applicable oversight requirements</li><li>Support E-AIAB governance processes by providing technical input into initiative assessments, vendor evaluations, and POV planning</li></ul></li><li>Technical Leadership &amp; Enablement<ul><li>Provide technical mentorship, code and architecture reviews, and hands-on guidance to the AI Developer team</li><li>Define engineering best practices, coding standards, and DevOps/MLOps conventions for the AI team</li><li>Collaborate with external vendors, implementation partners, and cloud providers to assess solutions, conduct technical due diligence, and ensure delivery quality</li><li>Contribute technical expertise to vendor RFP/RFI processes, proof-of-concept evaluations, and contract assessments</li><li>Represent the company's AI technical standards in cross-functional project delivery teams and steering committees</li></ul></li><li>Stakeholder Engagement &amp; Communication<ul><li>Translate complex technical architecture concepts into clear, accessible language for business stakeholders, executive leadership, and non-technical audiences</li><li>Serve as the primary technical escalation point for AI platform issues, architecture deviations, and integration challenges</li><li>Collaborate with IT Business Partners and AI Champions to provide technical feasibility input into AI opportunity assessments</li><li>Participate in external pharmaceutical AI forums, cloud provider events, and technology conferences to maintain leading-edge awareness and contribute to the company's technical reputation</li></ul></li></ol></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, or related technical field</li><li>Master's degree in Artificial Intelligence, Data Science, Computer Science, or related discipline is preferred</li><li>Microsoft Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent cloud architecture certification is preferred</li><li>TOGAF or equivalent enterprise architecture certification is preferred</li><li>7-10 years of professional experience in IT, software engineering, data &amp; analytics, or AI/ML implementation</li><li>4-6 years of hands-on experience designing and delivering AI/ML solutions on cloud platforms (Azure, AWS, or GCP) in a production environment</li><li>Proven track record of owning end-to-end AI solution architecture in a complex, cross-functional enterprise environment</li><li>Experience with Microsoft Azure AI, Azure Machine Learning, and Microsoft 365 Copilot architecture and deployment is preferred</li><li>Pharmaceutical, healthcare, life sciences, or other regulated industry experience is preferred</li><li>Experience with GxP validation, 21 CFR Part 11, or regulatory technology compliance in an AI/ML context is preferred</li></ul><p>Skills:</p><p><strong>Technical Competencies:</strong></p><ul><li>AI/ML Architecture &amp; Solution Design</li><li>Cloud Platform Architecture (Azure / AWS / GCP)</li><li>ML Ops &amp; Model Lifecycle Management</li><li>Enterprise Integration &amp; API Design</li><li>Data Architecture &amp; Data Engineering</li><li>AI Governance, Ethics &amp; Responsible AI</li><li>Pharmaceutical Regulatory Compliance (GxP, FDA, EMA)</li></ul><p><strong>AI &amp; Technology Skills:</strong></p><ul><li>Deep expertise in AI/ML architecture patterns, including supervised/unsupervised learning, NLP, computer vision, generative AI, and LLM-based solution design</li><li>Strong hands-on proficiency with Azure AI Services, Azure Machine Learning, MLflow, or equivalent MLOps tooling</li><li>Solid experience designing and deploying generative AI solutions including RAG architectures, LLM orchestration (LangChain, Semantic Kernel), and enterprise copilot patterns</li><li>Strong command of enterprise integration architecture including REST APIs, event-driven architecture, message queues, and middleware platforms</li><li>Proficiency in cloud infrastructure design including IaC (Terraform, Bicep), containerization (Docker, Kubernetes), and CI/CD pipelines</li><li>Strong understanding of data architecture components including data lakes, lakehouses, feature stores, and vector databases</li><li>Working knowledge of pharmaceutical business processes including GxP operations, quality management systems, and regulatory affairs workflows (Preferred)</li><li>Solid understanding of AI governance frameworks, responsible AI principles, data privacy regulations (GDPR, HIPAA), and IT security principles relevant to AI deployment</li></ul><p></p></section>