Barcelona, Catalunya, España
Hybrid
Introduction to role
The AI Cloud & Compute Services team, part of AstraZeneca's Enterprise AI unit, is responsible for orchestrating the compute strategy that underpins AstraZeneca's ambition to use AI in every step of the value chain – from discovering new compounds to patient safety systems. We focus on understanding what AstraZeneca truly needs for AI compute, ensuring that the most sustainable and cost-efficient options are leveraged across a multi-cloud landscape that is compliant by design.
We are looking for a Senior AI Platform Engineer to join our AI Cloud & Compute Services team. This is a technical leadership role focused on driving AI cloud and compute strategy - planning, provisioning, and optimisation across clouds and environments for cost-efficient scale. The ideal candidate will have industry-relevant experience delivering scalable AI/ML infrastructure and cloud computing services, with deep expertise across AWS, Azure, GCP, or equivalent platforms. You will be part of a collaborative, multidisciplinary team with the opportunity to shape how AstraZeneca provisions and operates AI compute at enterprise scale, directly enabling major AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning-led drug discovery, and software as a medical device systems.
As an Senior AI Platform Engineer with a passion for building complex, scalable systems, you will act as a key technical leader – driving small teams or projects, shaping AI compute and platform strategy, mentoring junior colleagues, and translating complex infrastructure challenges into actionable, high-impact solutions for the business.
Accountabilities
Multi-Cloud AI Services – Design and deliver multi-cloud AI compute services that are compliant by design, ensuring security, governance, and regulatory requirements are embedded from the outset.
AI Compute Capacity Strategy – Orchestrate AI compute capacity planning, provisioning, and optimisation across multiple clouds and environments to deliver cost-efficient, sustainable scale.
Sustainability & Cost Optimisation – Evaluate and recommend compute strategies that balance performance with sustainability and cost-effectiveness.
AI/ML Ops Embedding – Drive the standardisation of AI/ML deployment, monitoring, and lifecycle management across platforms, ensuring robust MLOps practices are embedded in all services.
Product Mindset – Operate with a product mindset: define clear roadmaps, SLAs, support models, and enablement programmes to drive adoption of compute services across business-facing teams.
Operational Simplification – Remove operational complexity so that delivery teams can focus on innovation rather than maintenance; ensure compliance-ready operations by design.
Technical Leadership & Mentoring – Act as a key technical leader, advising on best practices and innovative approaches, mentoring junior engineers, and shaping the strategic direction of AI cloud and compute services.
Stakeholder Collaboration – Collaborate with Data Scientists, Machine Learning Engineers, and platform teams across the company to understand their compute needs and deliver infrastructure that underpins their research and production workloads.
Governance & Compliance – Work closely with internal governance and compliance functions such as Cyber Security and Data Privacy to secure the compute estate without obstructing end-user productivity.
Essential Skills/Experience
B Sc/MSc/Ph.D. degree in Computer Science or a related quantitative or analytical field. Experience as a founder, entrepreneur, or experienced consultant will be considered equally.
Significant demonstrable experience working with AWS, Azure, GCP, or similar multi-cloud environments at enterprise scale.
Deep expertise in AI/ML compute infrastructure – including GPU provisioning, distributed training environments, and high-performance computing for AI workloads.
Demonstrable experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent) for deploying and managing AI/ML infrastructure at scale.
Strong experience with MLOps practices – building pipelines to accelerate and automate model deployment, monitoring, and lifecycle management.
Experience with cost management and optimisation of cloud compute resources, including FinOps principles and sustainability-focused compute strategies.
Experience operating with a product mindset: defining roadmaps, SLAs, and support models for platform/infrastructure services.
Experience using DevOps to enable automation strategies and reduce operational complexity.
Experience working with internal security standards and frameworks, especially within a medical, clinical, or pharmaceutical context.
Experience working with GxP-compliant life science systems will be looked upon favourably.
Proven ability to provide technical leadership, mentor junior colleagues, and drive strategic direction within a team or project.
Creative, collaborative, and resilient.
Desirable Skills/Experience
Experience with GPU orchestration & compute pooling such as NVIDIA Run:ai or equivalent to enable external platforms to securely trigger and queue workloads into shared GPU pools.
Experience with self-hosted AI inference infrastructure automating and operating self-hosted inference layers, including model serving orchestration, scaling, lifecycle management, and multi-tenant access control.
Experience shaping LLM deployment strategies, including model selection, serving infrastructure, and cost/sustainability trade-off analysis.
Familiarity with multi-cloud governance frameworks and compliance-by-design architectures.
Experience working in an Agile team with knowledge of product or platform-focused delivery.
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.
At AstraZeneca, we leverage technology to impact patients and ultimately save lives. As a purpose-led global organization, we push the boundaries of science to discover and develop life-changing medicines. Our work has a direct impact on patients, transforming our ability to develop these medicines. We empower the business to perform at its peak by combining cutting-edge science with leading digital technology platforms and data. Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Here you can innovate, take ownership, and explore new solutions in a dynamic environment. With investment behind us, there's no slowing us down!
Ready to make a meaningful impact? Apply now and be part of our journey!
Date Posted
14-jul-2026Closing Date
28-jul-2026AstraZeneca 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.
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