Director, Enterprise AI Engineering

Introduction: 

AstraZeneca is seeking a Director, Enterprise AI Engineering with exceptional depth in modern AI. We require someone who understands how models work at a fundamental level, not just how to apply them, but why they behave the way they do, where they fail, and how to design something better. Someone whose knowledge of the field is deep enough to distinguish genuine advances from incremental work, and current enough to know where the boundaries are. 

This person must also ship. We need a leader who translates that depth into production-grade AI systems at pace, leading a team of specialist engineers to solve, build, and deploy solutions on complex, high-impact problems. Research depth and engineering rigor in the same individual. 

This is a hybrid role based in Gothenburg, you will lead a team of AI Engineers and serve as a member of the AI Engineering Leadership Team. Candidates will be assessed on both their technical and leadership abilities, as a portfolio delivery lead, and a practicing engineer who raises engineering standards and leads by example. ​You will collaborate with product, architecture, and platform teams, designers, and leaders to deliver production-grade AI services and assets. 

Technical depth is equally critical to this role as leadership and delivery. We require someone who operates at the level of the mathematics, the algorithms, and the code — daily — while leading others to do the same. 

Our AI Engineering team is a focused incubator of deep technical talent. We build high-impact, reusable, scalable, production-grade AI assets and incubated products across five thematic areas: 

• Systems Intelligence — Systematically uncover, encode, and exploit what makes AstraZeneca unique 

• Systems Optimization — Move AstraZeneca AI from predictive to prescriptive across all core areas of business operations and decision-making 

• Applied Deep Learning — Deep learning expertise deployed on multi-modal, imaging, and foundational modelling initiatives 

• Engineering Foundations — Cultivate and strengthen foundational engineering capabilities, cross-deployed and forward-deployed across the portfolio 

• Product Incubation — Incubate and scale solutions prior to hand-off to enterprise product run teams 

Key Responsibilities:  

• Lead and develop AI Engineers with PhDs and significant industry backgrounds, setting and holding an exceptional technical standard 

• Contribute hands-on to large, shared production codebases alongside your team 

• Provide deep technical guidance on AI system design — architecture, training, evaluation, orchestration, and deployment — with demonstrable depth in one or more AI sub-domains 

• Define and implement golden-path standards for AI product development, software engineering, and applied ML research 

• Drive operational excellence in production ML systems: reliability, observability, failure handling, monitoring, incident response 

• Maintain deep, current knowledge of the research landscape; critically evaluate and integrate methods with genuine production applicability 

• Curate the strategic backlog as a Leadership Team member, focusing on highest-impact problems 

• Partner with other engineering directors across the broader AI engineering landscape