Title:  Manager, AI Solution

Location: Amman, Jordan

Job Type: Full-time

Hashtag: #LI-AA2

About Us

For over 45 years, Hikma Pharmaceuticals has been putting better health within reach, every day, by creating high-quality medicines and making them accessible to those who need them. We are helping to shape a healthier world that enriches all our communities, and our global team of 9,500+ empowered employees are central to this mission.

As a trusted and reliable partner of over 800 high-quality generics, specialty and branded pharmaceutical products, we are driven to improve access to medicine. Through our 29 manufacturing plants, 9 R&D centers across the MENA, North America and Europe, our footprint allows us to play a critical role in serving patients. 

Description:

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.

If you want to be part of a team that cares about impact, this is the place for you.

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

Qualifications:

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)
• Master's degree in Artificial Intelligence, Data Science, Computer Science, or related discipline (Preferred)
• Microsoft Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent cloud architecture certification (Preferred)
• TOGAF or equivalent enterprise architecture certification (Preferred)

Experience

• 7–10 years of professional experience in IT, software engineering, data & analytics, or AI/ML implementation
• 4–6 years of hands-on experience designing and delivering AI/ML solutions on cloud platforms (Azure, AWS, or GCP) in a production environment
• Proven track record of owning end-to-end AI solution architecture in a complex, cross-functional enterprise environment
• Experience with Microsoft Azure AI, Azure Machine Learning, and Microsoft 365 Copilot architecture and deployment (Preferred)
• Pharmaceutical, healthcare, life sciences, or other regulated industry experience (Preferred)
• Experience with GxP validation, 21 CFR Part 11, or regulatory technology compliance in an AI/ML context (Preferred)
• Deep expertise in AI/ML architecture patterns, including supervised/unsupervised learning, NLP, computer vision, generative AI, and LLM-based solution design
• Strong hands-on proficiency with Azure AI Services, Azure Machine Learning, MLflow, or equivalent MLOps tooling
• Solid experience designing and deploying generative AI solutions including RAG architectures, LLM orchestration (LangChain, Semantic Kernel), and enterprise copilot patterns
• Strong command of enterprise integration architecture including REST APIs, event-driven architecture, message queues, and middleware platforms
• Proficiency in cloud infrastructure design including IaC (Terraform, Bicep), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong understanding of data architecture components including data lakes, lakehouses, feature stores, and vector databases
• Working knowledge of pharmaceutical business processes including GxP operations, quality management systems, and regulatory affairs workflows (Preferred)
• Solid understanding of AI governance frameworks, responsible AI principles, data privacy regulations (GDPR, HIPAA), and IT security principles relevant to AI deployment

Learn more about Hikma in Jordan hikma-jordan-factsheet-aug-2025-en.pdf