Director, Operations IT - AI Engineering

About AstraZeneca 

AstraZeneca is a global, innovation-driven BioPharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious disease. But we’re more than one of the world’s leading pharmaceutical companies. 

At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development. 

About the Operations IT team 

Operations IT is a global capability supporting the Global Operations organization across Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics, and Global External Sourcing and Procurement. We operate from key hubs in the UK, Sweden, the US, China, and our Global Technology Centers in India and Mexico. Our work directly impacts patients by transforming our ability to develop life-changing medicines, combining cutting-edge science with leading digital technology platforms and data.

About the role

We are seeking a Director-level AI Engineer, operating in a “forward-deployed” model, to set the technical direction and guide delivery excellence across AstraZeneca’s Generative AI, AI Agent, and Digital Twin initiatives. Acting as the technical authority and trusted advisor across multiple programmes, you will embed with business stakeholders and delivery teams to translate ambition into deployable, production-grade solutions. Your deep technical credibility, breadth of market knowledge across emerging AI capabilities, and ability to influence without formal authority will be essential to raising the bar on how AI is designed, built, and delivered. This is an individual leadership role, with no direct reports — but with enterprise-wide accountability for technical quality, standards, and delivery excellence. 

Key Responsibilities 

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.

Date Posted

09-oct-2026

Closing Date

23-oct-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.