Job Description
Roles & Responsibilities
We are looking for a talented Manager, AI Solution to join us. At Hikma you ll be supported by a culture of progress and belonging where people are encouraged to develop, wellbeing is prioritised and our inclusive approach values contributions from all. We re seeking candidates who embody our values: Innovative, driven to keep learning; Caring, genuinely compassionate in their work; and Collaborative, eager to solve problems together.
Key Responsibilities:
- 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
- Collaborate with the Architecture advisory board to ensure the AI architecture roadmap is aligned with Hikma's overall digital transformation strategy and enterprise IT architecture principles
- Evaluate emerging AI technologies, frameworks, and platforms, providing technical direction and recommendations to senior IT and business stakeholders
- Lead architectural governance for all AI initiatives, ensuring solutions adhere to approved standards, security requirements, regulatory constraints, and scalability principles
- Define and maintain the enterprise AI technology stack including cloud AI services (Azure, AWS, GCP), MLOps platforms, data platforms, and integration middleware
- Architect end-to-end AI solutions across Hikma's key business domains including Manufacturing, Quality & Regulatory Affairs, R&D, Commercial, Supply Chain, HR, and Finance
- Produce high-quality architecture deliverables including solution design documents, architecture decision records (ADRs), technical specifications, data flow diagrams, and integration architecture blueprints
- Lead technical design reviews and architecture assessments for all AI initiatives in the portfolio, ensuring fitness for purpose, scalability, and compliance
- Define AI integration patterns with enterprise systems including SAP, MES, LIMS, CRM, and M365 ecosystems, ensuring seamless interoperability
- Guide AI Developers in translating architecture designs into well-structured, maintainable, and production-ready solutions
- Oversee the design of MLOps pipelines including model training, validation, deployment, monitoring, and retraining workflows
- Own the architecture and governance of enterprise AI platforms including Microsoft Azure AI, Azure Machine Learning, Microsoft 365 Copilot, and other approved AI tooling
- Define cloud infrastructure architecture for AI workloads including compute, storage, networking, and security configurations aligned with Hikma IT standards
- Establish standards for model lifecycle management including versioning, registry, performance monitoring, drift detection, and retraining triggers
- 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
- Ensure AI platforms meet GxP validation, 21 CFR Part 11, and audit trail requirements where applicable
- Embed regulatory and compliance requirements including FDA AI/ML guidance, EMA requirements, GxP, GDPR, and HIPAA into AI architecture design and review processes
- Define and enforce responsible AI architectural guardrails including model explainability, bias detection, fairness assessments, and human-in-the-loop design patterns
- Maintain AI architecture governance documentation including standards, patterns, approved toolsets, and deviation processes within the enterprise AI knowledge repository
- Coordinate with IT Security, Data Privacy, Legal, Quality Assurance, and Regulatory Affairs to ensure AI solutions meet all applicable oversight requirements
- Support E-AIAB governance processes by providing technical input into initiative assessments, vendor evaluations, and POV planning
- Provide technical mentorship, code and architecture reviews, and hands-on guidance to the AI Developer team
- Define engineering best practices, coding standards, and DevOps/MLOps conventions for the AI team
- Collaborate with external vendors, implementation partners, and cloud providers to assess solutions, conduct technical due diligence, and ensure delivery quality
- Contribute technical expertise to vendor RFP/RFI processes, proof-of-concept evaluations, and contract assessments
- Represent Hikma's AI technical standards in cross-functional project delivery teams and steering committees
- Translate complex technical architecture concepts into clear, accessible language for business stakeholders, executive leadership, and non-technical audiences
- Serve as the primary technical escalation point for AI platform issues, architecture deviations, and integration challenges
- Collaborate with IT Business Partners and AI Champions to provide technical feasibility input into AI opportunity assessments
- Participate in external pharmaceutical AI forums, cloud provider events, and technology conferences to maintain leading-edge awareness and contribute to Hikma's technical reputation
Desired Candidate Profile
We are looking for candidates whose experience and skills align closely with the qualifications outlined below:
- [Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, or related technical field (Required)/li>
- Master's degree in Artificial Intelligence, Data Science, Computer Science, or related discipline (Preferred)/li>
- Microsoft Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent cloud architecture certification (Preferred)/li>
- TOGAF or equivalent enterprise architecture certification (Preferred) /li>