وظائف مطورى واجهة مستخدم

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Syarah is a leading e-commerce platform in the automotive sector, transforming the car buying experience by offering a seamless, transparent, and fully digital journey.<br> The company is committed to innovation, operational excellence, and delivering exceptional customer service across its markets.<br> We are looking for a data-driven Product Manager to lead product initiatives across our platform.<br> This role requires strong ownership, analytical thinking, and the ability to deliver measurable impact in a fast-paced environment.<br> Key Responsibilities Own and drive end-to-end product lifecycle from discovery to delivery Define product requirements, write clear user stories, and manage backlog (Jira) Work closely with cross-functional teams (Engineering, Design, Operations, Finance, CX, Marketing) Analyze data and user behavior to inform decisions and prioritize initiatives Design, optimize, and iterate on product workflows and user journeys Run experiments (A/B testing) to validate hypotheses and improve performance Define, track, and report on KPIs and product impact Identify operational and product gaps and propose scalable solutions Manage stakeholder expectations and ensure alignment across teams 2–4 years of experience in Product Management Strong data-driven mindset and analytical skills Hands-on experience with Agile/Scrum methodologies Ability to write clear tickets, user stories, and manage backlog effectively Experience in A/B testing and experimentation Strong understanding of KPIs, funnels, and product impact measurement Experience in workflow design and process optimization Strong stakeholder management and communication skills Familiarity with tools like Jira, Confluence, Miro (or similar) Nice to Have Experience in E-commerce or marketplace products Familiarity with ERP systems or internal tools Experience working in cross-functional, operations-heavy environments</span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history 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 Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<p>The Quality Assurance and Documentation Engineer is responsible for ensuring application quality, stability, and knowledge continuity across all systems. This role combines hands-on testing with structured technical documentation, ensuring that functional behavior, system architecture, integrations, and processes are fully understood, documented, and repeatable.</p><p>Responsibilities:</p><p><strong>Quality Assurance &amp; Testing</strong></p><ul><li>Plan, design, and execute functional, regression, and smoke test cases for web, API, Windows client, and mobile applications.</li><li>Validate business requirements against implemented features and acceptance criteria.</li><li>Test multi-tenant scenarios, role-based access, and permission logic.</li><li>Validate integrations with external systems (e.g., payment gateways).</li><li>Perform data validation testing on SQL Server to ensure data accuracy and integrity.</li><li>Identify, log, and track defects using Jira / Azure DevOps.</li><li>Verify bug fixes and prevent regressions.</li><li>Support User Acceptance Testing (UAT) and pre-production validation.</li></ul><p><strong>Release &amp; Environment Validation</strong></p><ul><li>Validate deployment readiness for QA, UAT, and Production environments.</li><li>Perform post-deployment verification and smoke testing.</li><li>Support hotfix validation and emergency releases.</li><li>Coordinate with DevOps and Development teams to ensure environment stability.</li></ul><p><strong>Test Documentation &amp; Standards</strong></p><ul><li>Create and maintain: test plans, test cases, test scenarios, and regression suites</li><li>Define and improve QA processes and testing standards.</li><li>Ensure repeatable, auditable testing practices aligned with SDLC.</li></ul><p><strong>Application &amp; Technical Documentation</strong></p><ul><li>Document application components including: modules and features, application flows, APIs and integrations, data flows and dependencies, and background jobs and scheduled processes.</li><li>Maintain up-to-date documentation for: architecture overview, deployment flows, and environment configurations</li><li>Ensure documentation is structured, accessible, and version controlled.</li><li>Work closely with developers to capture technical knowledge accurately.</li></ul><p><strong>Knowledge Management &amp; Transition</strong></p><ul><li>Lead documentation activities during vendor transition and knowledge transfer.</li><li>Ensure critical system knowledge is captured and not retained by individuals.</li><li>Support onboarding of new team members using documented materials.</li><li>Actively reduce single-point-of-failure risks.</li></ul><p><strong>SDLC &amp; Process Compliance</strong></p><ul><li>Ensure QA activities are embedded in the SDLC.</li><li>Validate that acceptance criteria are met before release approval.</li><li>Support sprint planning by estimating QA effort.</li><li>Participate in retrospectives to improve quality processes.</li></ul><p><strong>Tools &amp; Automation (Progressive)</strong></p><ul><li>Support test automation initiatives where applicable.</li><li>Collaborate with DevOps on CI/CD quality gates.</li><li>Identify opportunities to improve testing efficiency and coverage.</li></ul><p><strong>Collaboration &amp; Communication</strong></p><ul><li>Work closely with development team lead, developers, and technical delivery lead, DevOps &amp; Infra teams.</li><li>Provide clear quality status and risk visibility.</li><li>Escalate quality risks early.</li></ul><p><strong>Job Relations:</strong></p><p>Reports to IT Manager. Works closely with Development, DevOps, Infra, and Product teams. Coordinates with business stakeholders during UAT.</p><p><strong>Desired Candidate Profile</strong></p><p>Bachelor's degree in computer engineering, computer science, or a related field.</p><p>3-6 years of experience in QA or software testing, and documentation</p><p>Strong understanding of SDLC and testing methodologies.</p><p>Experience testing: Web applications, APIs, and SQL-based systems</p><p>Strong documentation and communication skills.</p><p>Detail-oriented with strong analytical skills.</p><p><strong>Competencies:</strong></p><ul><li>Experience with enterprise or multi-tenant systems.</li><li>Experience documenting legacy systems.</li><li>Exposure to ASP.NET Zero / abp.io.</li><li>Experience working with distributed teams.</li><li>Familiarity with basic test automation concepts.</li></ul><p><strong>Skills &amp; Languages:</strong></p><ul><li>Proficiency with Agile tools (e.g., Jira)</li><li>Understanding of software development life cycle and agile methodologies.</li><li>Good knowledge of partner/system integration principles (APIs, data exchange formats, etc.)</li><li>Fluent in English (required).</li><li>Arabic proficiency (preferred).</li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><span><span><u>About the Job</u></span></span><br></span><p><span>As a <b>Mid-</b></span><b><span>Senior Full Stack Java Developer</span></b><span> at Aspire, you will design, develop, and maintain scalable web applications using Java, Spring Boot, and modern frontend technologies. You will work across the full software development lifecycle, developing robust backend services and user-friendly frontend applications while collaborating closely with QA, DevOps, product, and business teams.</span><br></p><br><span><span><u>What You Will Do</u></span></span><br><ul><li><span>Design, develop, and maintain scalable web applications using Java and Spring Boot.</span><br></li><li><span>Develop and maintain RESTful APIs and microservices.</span><br></li><li><span>Build responsive and user-friendly frontend applications using React.js or Angular.</span><br></li><li><span>Integrate frontend applications with backend APIs and third-party services.</span><br></li><li><span>Design, develop, and optimize SQL databases.</span><br></li><li><span>Write clean, maintainable, and reusable code following best practices and design patterns.</span><br></li><li><span>Perform unit, integration, and API testing.</span><br></li><li><span>Participate in code reviews, technical discussions, and solution design.</span><br></li><li><span>Troubleshoot and resolve application and production issues.</span><br></li><li><span>Work closely with QA, DevOps, product, and business teams.</span><br></li><li><span>Participate in Agile ceremonies and contribute throughout the SDLC.</span><br></li><li><span>Support CI/CD pipelines and application deployments.</span><br></li></ul><span><span><u>What You Will Need</u></span></span><br><ul><li><span>4–7+ years of professional software development experience.</span><br></li><li><span>Strong proficiency in Java 8/11/17+.</span><br></li><li><span>Strong experience with Spring Boot, Spring MVC, and Spring Security.</span><br></li><li><span>Hands-on experience with Microservices architecture.</span><br></li><li><span>Strong knowledge of REST APIs and web services.</span><br></li><li><span>Experience with React.js or Angular.</span><br></li><li><span>Strong JavaScript/TypeScript, HTML5, and CSS3 skills.</span><br></li><li><span>Strong SQL knowledge and experience with databases such as PostgreSQL, MySQL, or Oracle.</span><br></li><li><span>Experience with Git and version control.</span><br></li><li><span>Experience with Docker and CI/CD tools.</span><br></li><li><span>Good understanding of software architecture and design patterns.</span><br></li><li><span>Experience with JUnit/Mockito or similar testing frameworks.</span><br></li><li><span>Good understanding of Agile/Scrum methodologies.</span><br></li><li><span>Awareness or knowledge of IT security best practices as defined by ISO/SOC or similar standards.</span><br></li></ul><span><u><span>Why Aspire</span></u></span><br><ul><li><span>Be part of a (Remote is here-to-stay) organization</span><br></li><li><span>Work and learn from great minds</span><br></li><li><span>Explore new opportunities to learn and grow every day by attending technical and nontechnical training</span><br></li><li><span>Get market exposure by working with international tech leaders</span><br></li><li><span>Nursery reimbursement benefit</span><br></li><li><span>Attend virtual and onsite international tech conferences</span><br></li><li><span>Exposure to work in an IT environment that adheres to rigorous security and compliance standards defined by ISO / SOC</span><br></li></ul><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>Job Requisition ID #</b></p><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>26WD99671<p><i>The ATL operates within Autodesk’s Sales Evolution framework, partnering closely with Account Executives (AE/AR) to drive pipeline progression, deal velocity, and long-term customer value.</i></p><br><p><i>Success in this role is measured by the ability to prioritise effectively, orchestrate technical engagements at scale, influence deal outcomes, and drive repeatable, high-impact technical strategies across accounts.</i></p><br><p><u><b><span>Main Responsibilities:</span></b></u></p><br><p><b><span>Technical Strategy &amp; Account Alignment:</span></b></p><br><ul><li><p>Own the technical strategy across assigned territory accounts</p><br></li><li><p>Align Autodesk solutions to customer business outcomes, challenges, and priorities</p><br></li><li><p>Translate discovery insights into clear technical approaches and engagement plans</p><br></li><li><p>Balance depth vs. scale-ensuring the right level of technical investment per opportunity</p><br></li></ul><p><b><span>Opportunity Orchestration &amp; Execution:</span></b></p><br><ul><li><p>Act as the central coordination point for all technical engagement within opportunities</p><br></li><li><p>Determine which technical specialists (TSS/partners) to engage, when, and at what depth</p><br></li><li><p>Guide opportunity progression through structured technical validation and alignment</p><br></li><li><p>Ensure consistency in messaging, approach, and solution positioning across engagements</p><br></li></ul><p><b><span>Discovery Leadership &amp; Value Framing:</span></b></p><br><ul><li><p>Lead or shape discovery for strategic and high-impact opportunities</p><br></li><li><p>Ensure discovery connects customer pain points to measurable business outcomes</p><br></li><li><p>Leverage tools such as Value Management Platform (VMP) and Customer Outcome Proposals (COP) to articulate ROI and solution value</p><br></li><li><p>Elevate conversations from product to workflow, platform, and business transformation</p><br></li></ul><p><b><span>Commercial &amp; Deal Support:</span></b></p><br><ul><li><p>Partner with AE/AR to shape deal strategy and technical win themes</p><br></li><li><p>Identify expansion, cross-sell, and upsell opportunities through technical insight</p><br></li><li><p>Support deal progression through clarity, risk mitigation, and stakeholder alignment</p><br></li><li><p>Contribute to forecast confidence through structured technical qualification</p><br></li></ul><p><b><span>Customer Engagement &amp; Executive Influence:</span></b></p><br><ul><li><p>Engage with customer stakeholders across technical and business levels</p><br></li><li><p>Act as a trusted advisor for digital transformation, platform adoption, and workflow optimisation</p><br></li><li><p>Influence customer decision-making through structured, outcome-driven conversations</p><br></li><li><p>Support executive-level discussions for strategic accounts where required</p><br></li></ul><p><b><span>Technical Leadership &amp; Enablement:</span></b></p><br><ul><li><p>Provide direction and guidance to Technical Specialists (TSS) and partners</p><br></li><li><p>Drive consistency through reuse of proven patterns, playbooks, and assets</p><br></li><li><p>Enable sellers and partners with clear technical narratives and engagement approaches</p><br></li><li><p>Mentor team members and contribute to capability uplift across the region</p><br></li></ul><p><b><span>Regional Execution &amp; Operating Model Adoption:</span></b></p><br><ul><li><p>Champion the AE/AR → ATL → TSS engagement model</p><br></li><li><p>Drive adoption of structured workflows, discovery approaches, and technical standards</p><br></li><li><p>Capture and share learnings to improve repeatability and scalability</p><br></li><li><p>Provide feedback to leadership on gaps, opportunities, and field insights</p><br></li><li><p>Contribute to the ongoing success and cohesion of the regional Technical Sales team</p><br></li></ul><p><u><b><span>Minimum Qualifications:</span></b></u></p><br><ul><li><p><b>7-10+ years of experience in technical sales, solution consulting, or similar customer-facing roles</b></p><br></li><li><p><b>Strong understanding of AEC workflows across design, coordination, and construction</b></p><br></li><li><p><b>Familiarity with Autodesk ecosystem including:</b></p><br><ul><li><p><b>Revit, Navisworks, Civil 3D</b></p><br></li><li><p><b>Autodesk Construction Cloud (Docs, Build, BIM Collaborate Pro)</b></p><br></li><li><p><b>Autodesk Platform Services (APS / Forge)</b></p><br></li></ul></li><li><p>Experience positioning integrated, end-to-end workflows and platform strategies</p><br></li><li><p>Strong ability to connect technical solutions to business outcomes</p><br></li><li><p>Demonstrated ability to coordinate and influence cross-functional teams</p><br></li><li><p>Strong communication, stakeholder management, and strategic thinking skills</p><br></li></ul><p><u><b><span>Preferred Qualifications:</span></b></u></p><br><ul><li><p>Experience operating in an orchestration or overlay technical role</p><br></li><li><p>Familiarity with value-selling methodologies and ROI-based positioning</p><br></li><li><p>Experience working in hybrid (direct + partner-led) sales environments</p><br></li><li><p>Exposure to enterprise customers and digital transformation initiatives</p><br></li><li><p>Experience mentoring or leading technical teams</p><br></li></ul><p><span><b><b>Learn More</b></b></span></p><br><p><b><span>About Autodesk</span></b></p><br><p><span>Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.</span></p><br><p><span>We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.</span></p><br><p><span>When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!</span></p><br><p><b><span>Salary transparency</span></b></p><br>Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.<br><p><b>Belonging</b><br>We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: <span><u>https://www.autodesk.com/company/global-belonging</u></span></p><br><p><b>Are you an existing contractor or consultant with Autodesk? </b></p><br><p>Please search for open jobs and apply internally (not on this external site).</p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br>What this opportunity involves: We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history 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 Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT: Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for: 8+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard: Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidEffort estimate Tasks for this project are estimated to take 30 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation: Up to $150/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~30 hours each; you set your own schedule.<br></span> </div>

<p><h4>Please submit your CV in English and indicate your level of English proficiency.<\/h4>\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>8+ 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 30 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><\/p><p><\/p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history 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 Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<p><h4>Please submit your CV in English and indicate your level of English proficiency.<\/h4>\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>8+ 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 30 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><\/p><p><\/p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Key Responsibilities:</p><p>System &amp; Infrastructure Support:</p><ul><li>Troubleshoot, diagnose, and resolve all application, user and system issues.</li><li>Ensure high performance of Retail systems across Head Office and all sites.</li><li>Provide support for MS SQL Server-based systems (Head Office, Back Office, POS).</li></ul><p><br></p><p>User &amp; Client Support:</p><ul><li>Liaise with users at Head Office and fuel stations to resolve technical issues.</li><li>Provide training and guidance to users on system functionalities as required.</li><li>Work closely with vendors and external support teams for any third-party system issues.</li></ul><p>Required Skills &amp; Qualifications:</p><p>Technical Expertise:</p><ul><li>background in infrastructure support (networking, servers, storage, cloud, security).</li><li>Familiarity with POS systems, bank terminals, etc.</li><li>Experience of Implement, test, configure, troubleshooting and supporting application.</li><li>Experience in Providing technical support to end-user as per IT related issues</li><li>Experience in Writing queries and manage MS SQL and writing scripts.</li><li>Good understanding of Web Services, API and IP based protocols</li><li>Knowledge of networking protocols, firewalls, VPNs, and other network management tools.</li></ul><p><br></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p>Experience:</p><ul><li>Minimum 3+ years of experience in IT support roles.</li><li>Experience working with retail systems or similar environments with distributed sites.</li></ul><p><br></p><p>Personal Attributes:</p><ul><li>Strong leadership qualities with the ability to motivate and develop a high-performing support team.</li><li>Able to manage high-pressure situations and lead incident responses.</li><li>Self-motivated, detail-oriented, and able to work independently when required.</li></ul><p><br></p><p>Other Considerations:</p><ul><li>Ability to work in an on-call &amp; shift rotation, if necessary, to provide after-hours support</li></ul><p><br></p></div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history 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 Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history 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 Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<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>\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>\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>

<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>\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>\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>

<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>