Director, Enterprise AI Engineering

Introduction:

AstraZeneca is seeking a Director, Enterprise AI Engineering with exceptional depth in modern AI. Werequiresomeone 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.

Our AI Engineering team is a focused incubator of deep technical talent. We build high-impact, reusable, scalable, production-grade AIassetsand 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 learningexpertisedeployed 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

KeyResponsibilities:

• 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

• Providedeep 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

• Translate customer and business demands into clear, actionable software requirements

EssentialSkills/Experience:

• Significant industry experience delivering production AI systems in large, complexorganisations— able to raise the technical bar under real portfolio constraints and enterprise governance

• Deepexpertisein the internals of modern AI systems; able to reason about modelbehaviourfrom first principles, not only empirically

• Demonstrable depth in at least one AI sub-domain (e.g., optimization, language, multi-modal, foundational models, agentic systems)

• Current grasp of the research landscape; able to critically assess and apply work from leading academic venues

• Experience designing and delivering multi-componentAI systems and services

• BSc/MSc/PhD in Computer Science or related quantitative field

• Proven leadership of engineers with PhDs and significant industry backgrounds

• Active contributor to large-scale production codebases, shared libraries, or SDKs

• Advanced Python; familiarity database solutions (SQL, NoSQL, graph)

• Strong software engineering practice: architecture, CI/CD, unit testing, OOP, Git

• Algorithm design,optimisation, and scaling from first principles

• Cloud platform experience for ML development, API design, and deployment

• Able to engage senior business and technical stakeholders with equal credibility

• Experience in regulated or compliance-sensitive environments

WhatWeOffer:

• A high-impact AI engineering team solving consequential problems in healthcare

• A Leadership Team seat with real influence over strategic and technical direction

• Access tocutting-edgeAI technologies and uniquely valuable data

• Professional growth in a company committed to turning ideas into life-changing medicines

• Competitive compensation and benefits