Director, Operations IT - AI Engineering

Technical Guidance & Standards (~40%)

• Define and evolve reference architectures, design patterns, and delivery playbooks for GenAI, AI Agents, and Digital Twins, ensuring consistency and reuse across teams.
• Act as the technical authority for AI engineering practice, setting the quality bar for code, architecture, and production readiness.
• Establish and chair technical review forums and communities of practice to share learning and raise capability across engineering teams.
• Track the fast-evolving AI product and vendor landscape (LLMs, agent frameworks, digital twin platforms) and translate relevant innovations into practical guidance.

Delivery Excellence (~40%)

• Embed directly ("forward-deployed") in critical or at-risk programmes to unblock technical challenges, review designs/code, and course-correct delivery before issues compound.
• Partner with project and programme leads to assess risks, requirements, and dependencies; anticipate problems and advise on mitigation strategies.
• Provide hands-on technical consultancy to business stakeholders to help estimate, prioritize, and scope AI initiatives realistically.
• Conduct design and code reviews across multiple concurrent initiatives to ensure solutions are secure, scalable, and production-ready.

Stakeholder Partnership & Influence (~20%)

• Engage senior internal stakeholders (POs, business partners, architects, other engineering teams) and external partners/vendors to shape the AI delivery agenda.
• Collaborate with the innovation team to identify, prototype, and socialize new strategic technical capabilities.
• Mentor and upskill engineers across teams, even without formal line management responsibility, acting as a technical coach and escalation point.
• Represent AI Engineering in governance, architecture, and leadership forums, articulating technical trade-offs to both technical and non-technical audiences.

Qualifications

Required:

• Bachelor's degree in operations research, mathematics, computer science, or a related quantitative field.
• At least 10 years of professional experience delivering ML/AI projects, including at least 5 years operating as a technical lead, principal engineer, or architect across multiple concurrent initiatives.
• Demonstrated track record of setting technical direction and raising delivery standards across teams without formal line management authority.
• Advanced expertise in Python and familiarity with database systems (e.g., Snowflake, Neo4j databases).
• Deep, hands-on expertise in Generative AI and AI Agents, including designing, building, and productionizing agentic systems at scale.
• Strong understanding of software development (frontend, backend), algorithms, optimization, and scaling.
• Excellent communication, business analysis, and stakeholder-influencing skills, with the credibility to advise senior business and technical leaders.

Nice to Have:

• Master's or PhD in a relevant quantitative field.
• Experience with AWS cloud services and cloud engineering.
• Knowledge of LangGraph or other agent orchestration frameworks.
• Experience with Digital Twin platforms (e.g., Azure Digital Twins, NVIDIA Omniverse, AnyLogic).
• Experience establishing technical governance structures, centers of excellence, or architecture review boards.
• Conference speaking, published thought leadership, or open-source contributions in GenAI/agentic AI.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.