Senior Director, AI Cloud & Compute Services

Introduction to the role

Help shape and scale a

multi-cloud AI platform

that speeds up the discovery and development of life-changing medicines! This role leads the strategy, build and evolution of enterprise compute and cloud-native AI services used every day by scientists and engineers across the business.

The focus is clear: turn ambitious ideas into

secure, compliant and reusable capabilities

that work at scale. Success in this role means connecting data foundations, AI technologies and smarter ways of working into one strong platform that helps teams move faster, with less friction and more confidence. It is a chance to set direction, remove blockers and drive adoption across a global organisation!

What this role will do

This role will define how AI and machine learning services are used across

AWS, Azure and GCP

, creating a simpler and more consistent experience across multiple cloud environments. Managed services such as

SageMaker, Azure ML and Vertex AI

will be brought together through strong architecture, Infrastructure as Code and practical integrations that make secure adoption easier.

Enterprise compute strategy will sit at the heart of the role, balancing

performance, cost, resilience and compliance

. The platform will need repeatable, auditable Terraform foundations that support AI services with the rigour required in regulated environments.

The role will also unify cloud-native AI services into a more consistent platform model, with shared patterns, governance and guardrails that reduce duplication and support faster delivery. Rather than leaving teams to reinvent solutions, the platform will provide dependable standards that teams can adopt and scale.

Leadership is a major part of the remit. A high-performing team of

AI platform and DevOps specialists

will be built, coached and challenged to raise the bar. An automation-first mindset, strong engineering discipline and compliance-by-design approach will be central to how the team operates.

The role also carries ownership for budgets and resourcing across

headcount, cloud consumption, outsourced services and specialist partners

. Strong FinOps thinking will be important to improve visibility, control spend and maximise value.

Alongside delivery, this role will champion enterprise-wide adoption. Proven platform patterns, reusable components and successful ideas will be scaled across functions and geographies, helping more teams work with greater speed, safety and efficiency.

Close partnership with leaders across

R&D, engineering, security and compliance

will be essential. The role will translate scientific and business priorities into technical strategy, practical roadmaps and measurable outcomes.

Essential Skills/Experience

We’re looking for someone with 15+ years of experience, including at least 5 years in senior technical leadership roles focused on AI platforms, cloud infrastructure, or cloud-native AI services, ideally in regulated industries. This person will bring a strong track record of leading large-scale platform transformations and helping teams navigate complex, multi-year change with clarity and confidence.

Deep expertise across

AWS, Azure and GCP

is expected, especially in AI and machine learning services. Strong hands-on knowledge of

Terraform

is also important, including enterprise module design, multi-cloud implementation, CI/CD integration, and state management and governance.

This role calls for broad compute leadership experience, including

Kubernetes, serverless and event-driven architectures, GPU optimisation for machine learning workloads, auto-scaling and cost optimisation

. A strong engineering background with hands-on capability in

Python, Bash and PowerShell

will be valuable.

Experience in

GxP-compliant systems

is important, ideally in life sciences or pharmaceutical settings, including documentation and validation requirements. Strength in DevOps and GitOps tooling is also needed, covering areas such as

Git, GitHub Actions, Azure DevOps, Docker and Kubernetes

.

A solid grasp of

cloud security, identity and access management, and data governance

across multi-cloud environments is essential. Strong communication and stakeholder leadership skills matter just as much, especially the ability to influence across a large global organisation.

Desirable Skills/Experience

Experience with

MLOps practices and platforms

such as MLflow, Kubeflow and feature stores would be useful, as would knowledge of observability tooling including

Datadog, Prometheus, Grafana and CloudWatch

.

Background in

FinOps, large-scale data pipelines, pharmaceutical R&D workflows, scientific computing

, or contributions to open-source cloud-native or Infrastructure as Code projects would also stand out.

Working at AstraZeneca

At AstraZeneca, unexpected combinations of talent often lead to the most powerful ideas. Bringing diverse teams together creates the energy, pace and challenge needed to do meaningful work. That is why in-person collaboration remains an important part of how we operate, with a minimum of

three days per week in the office on average

. There is flexibility too, with room for individual circumstances and balanced ways of working.

Why AstraZeneca

This is a place where

science and technology meet with real purpose

. The work does not stop at experimentation or prototypes. Ideas are tested, strengthened and scaled into capabilities that make a tangible difference for patients.

Teams here are global, ambitious and highly collaborative. The environment combines

high standards, serious investment and a strong sense of support

. Bold thinking is encouraged. Progress is expected. Kindness matters too! For leaders who want to simplify complexity, build strong platforms and create lasting enterprise impact, there is real room to do it here.