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Director, AI ML and Cloud Security

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: GSK
Full Time position
Listed on 2026-10-26
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 140000 - 210000 GBP Yearly GBP 140000.00 210000.00 YEAR
Job Description & How to Apply Below

Why Us! At GSK, we unite science, technology and talent to get ahead of disease together. We are a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together. We’re proud to be leading a healthcare revolution, and we’re looking for people who can help us deliver on our ambition.

Director, AI ML & Cloud Security Job Purpose

Lead AI engineering delivery for Cyber Architecture and Solutions: the team that builds what AI Architecture designs and hands it to a vendor to operate. You own four work streams — agentic framework build, AI solution engineering, AI platform infrastructure and the data fabric pipeline — across seven engineers. You are accountable for build quality, test coverage and vendor handover readiness. You do not define architecture.

About

the team

AI ML and Cloud Security is the function through which GSK is transforming security itself. The team designs and builds the agentic framework, a multi-agent platform moving security services across the Chief Security Office from rule-based to AI-driven operation. It owns AI architecture and AI engineering end to end: the agent layer, LLM orchestration, the AI and ML platform, and the data fabric pipeline that CAS designs, builds and tests before a managed service vendor operates it.

The team also governs AI tool security posture, advises on cloud security across the Azure and GCP estate, and is the front door between GSK's business units and R&D and the technical AI function. AI security standards set here are binding on every AI initiative in GSK. Seventeen roles across the UK, India and the US.

What makes this role different

This is hands-on engineering leadership, not delivery management. You will review code, argue about orchestration patterns, and decide whether a build is genuinely ready for a vendor to run r engineers work in Lang Chain, Llama Index, vector databases and production Python on Kubernetes; if you cannot read that work critically you will not carry the team. The architecture is set by someone else and you will sometimes disagree with it — challenge it properly, then build it well.

Key Responsibilities
  • Own AI engineering delivery across agentic framework build, AI solution engineering, platform infrastructure and the data fabric pipeline.
  • Chair the fortnightly build review with the managed service vendor and sign or refuse the handover certificate for each agent and pipeline they take on.
  • Build AI-powered security capability including GenAI alert triage, automated threat investigation and LLM‑assisted analysis, and prove it works before it is trusted.
  • Hold the four workstream leads to a single release train, and arbitrate when agent and platform priorities compete for the same engineer.
  • Set the engineering standard the four work streams build to — test coverage thresholds, evaluation harness pass rates and the definition of handover‑ready — and audit against it at each release.
  • Ensure every build is tested, documented and packaged to the standard a managed service needs to operate it without Cyber Architecture and Solutions present.
  • Lead six engineers across India and the UK and manage dependencies across the agent, platform and delivery work streams.
  • Embed security controls by design to the binding AI security standards and secure sign‑off before release.
  • Act as the senior engineering voice in architecture reviews, challenging designs on buildability, testability and operability.
Why You

We are seeking professionals with the following required skills and qualifications to help us achieve our goals:

Basic Qualifications
  • Significant experience in cyber security or AI engineering, including leading technical teams across geographies — domain focus: AI Engineering;…
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