Senior Staff AI Infrastructure Engineer

Salary: £70,000 - 110,000 per year

Requirements:

• Were looking for a candidate with a PhD or an MSc with equivalent experience in a STEM subject.
• Extensive senior staff-level experience as an infrastructure, platform, or systems engineer for compute-intensive workloads, including setting architecture, standards, and technical direction for a team or function.
• Deep expertise across the AI compute infrastructure stack, including high-performance and GPU compute, storage and file systems, networking, container platforms and orchestration (such as Kubernetes), environment provisioning, and infrastructure-as-code (such as Terraform).
• Significant experience with hybrid on-premises and cloud architectures, including right-sizing, cost optimization, and designing for portability to avoid vendor lock-in.
• Expertise in providing infrastructure for large-scale AI workloads, including distributed training at scale.
• Understanding of security, access control, resilience and continuity, and rigorous systems operations (ITIL or equivalent service management).
• Strong collaboration and influencing skills with technical and non-technical stakeholders, including the ability to explain complex technical concepts clearly and mediate competing requirements.
• Experience mentoring or technically leading engineers and setting engineering principles.

Responsibilities:

• Own, define, and evolve a holistic, multilayer reference architecture spanning storage, compute, environments, and the platform stack, making appropriate use of vendor and integrator design patterns.
• Set the technical direction, strategy, and roadmap for AI infrastructure, aligning them with AI Enablement roadmaps and portfolio and research priorities.
• Partner with Data Excellence to further develop BIs Trusted Research Environment (TRE), ensuring it supports secure, compliant AI workloads on sensitive data and evolves to meet the AI Accelerators needs.
• Work with IT to shape enterprise infrastructure for large-scale AI, secure best-value services, and design for portability.
• Establish ways of working, onboard and mentor team members, and serve as a senior escalation point for complex AI infrastructure problems.
• Lead the AI Accelerators technical infrastructure strategy so our teams have the compute, storage, and platform infrastructure needed to train, fine-tune, and serve biomedical foundation models at scale.
• Lead architecture, standards, and practices for the compute and platform substrate, working with Computational Innovation data teams, IT, and cloud providers to help AI scientists and ML teams make the best use of available infrastructure.
• Contribute to the overall direction of the AI Enablement leadership team alongside the Senior Staff Data Engineer and Senior Staff MLOps Engineer.

Technologies:

• AI
• Cloud
• ITIL
• Kubernetes
• MLOps
• Security
• Terraform
• DevOps
• Support

More:

The AI Accelerator is based in London within Computational Innovation, our global organization spanning computational biology, human genetics, data excellence, and AI. We build production-quality AI capabilities to deepen understanding of disease biology and increase the probability of success by applying neural-based methods to heterogeneous, multimodal biomedical data. Our work aims to explain why disease occurs and may include patient segmentation using electronic health records and medical imaging, identifying therapeutic targets from omics data, predicting transcriptional changes caused by disease-associated variants, and simulating the effects of modulating targets. AI Infrastructure supports this work through compute, storage, and platform services, using both on-premises capabilities and cloud services. This senior technical leadership role is part of a strategic pharmaceutical research and development initiative focused on innovative therapies for areas of high unmet medical need. The role is hybrid, with approximately four days a week in the office. Boehringer Ingelheim has been recognized as a Top Employer in the UK, reflecting our commitment to a supportive workplace and strong people practices.

last updated 39 week of 2026