Director, Operations IT - AI Engineering

About the role

AstraZeneca is looking for a Director-level AI Engineer to set the technical direction and guide delivery excellence across its Generative AI, AI Agent and Digital Twin initiatives. Working in a forward-deployed model, the role acts as technical authority and trusted advisor across several programmes, embedding with business stakeholders and delivery teams to turn ambition into production-grade solutions. It is an individual leadership role with no direct reports.

Key responsibilities

• Define reference architectures, design patterns and delivery playbooks for GenAI, AI Agents and Digital Twins, and act as the technical authority for AI engineering practice
• Chair technical review forums and communities of practice, and track the AI product and vendor landscape to turn innovations into practical guidance
• Embed in critical or at-risk programmes to unblock technical challenges, review designs and code, and advise on risk mitigation
• Help business stakeholders estimate, prioritize and scope AI initiatives, and conduct design and code reviews
• Engage senior internal stakeholders and external vendors, collaborate with the innovation team, mentor engineers and represent AI Engineering in governance and leadership forums

Required profile

• 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 as a technical lead, principal engineer or architect
• Proven track record of setting technical direction and raising delivery standards without formal line management authority
• Nice to have: Master's or PhD, experience with AWS, LangGraph, Digital Twin platforms, and technical governance structures

Required skills

• Advanced Python and familiarity with database systems such as Snowflake and Neo4j
• Hands-on expertise in Generative AI and AI Agents, including agentic systems at scale
• Understanding of software development, algorithms, optimization and scaling