Associate Director - AI ML and Cloud Security - AI Agent Engineering

Overview

Associate Director, AI ML and Cloud Security - AI Agent Engineering at GSK. Owns the agent layer of the agentic framework: the build, not the design, with hands-on leadership of an agent engineering team.

What you'll do

• Own the agent layer: agent development pipeline, LLM integration, prompt-to-action engineering and agent lifecycle.
• Own agent evaluation and testing, including credible approaches to non-deterministic output.
• Build GenAI security use cases such as alert triage automation and threat summarisation.
• Develop reusable agent components that reduce effort on the next build.
• Build to AI Architecture's specifications and raise design problems rather than engineering around them.
• Apply the binding AI security standards to every agent (tool-invocation control, identity binding, least-privilege scoping) and secure sign-off before release.
• Prepare agent workstream handover packages to the standard the managed service needs.
• Hold AI Platform Engineering to the model-serving endpoints, vector index service levels and token budgets your agents depend on, and escalate when an agent outgrows them.
• Lead the agent engineers building the agent layer, and keep at least a third of your own week on code.
• Run the two-week shadow period where the vendor's operators work your agents under supervision, and hold the go-live gate until their runbook survives a deliberately injected failure.
• Lead your team in using approved AI tools to improve productivity and ways of working, role-modelling responsible use and following GSK's Responsible AI, privacy and security requirements.
• Mentor the agent engineers and set the engineering standard for the agent layer by example: code review, evaluation discipline and documentation quality.
• Apply GxP and data integrity expectations to agents that touch validated systems or the records they produce.

What you'll need

• 15+ years in cyber security or AI engineering in a regulated environment.
• Agent engineering depth: LLM integration, prompt-to-action engineering, multi-agent orchestration, tool and function calling, memory and state management, RAG retrieval, prompt and model version control and reusable agent components.
• Agent safety engineering: evaluation harnesses for non-deterministic behaviour, red-team testing, guardrails, human-in-the-loop checkpoints, containment and rollback.
• Building GenAI security use cases (alert triage automation, threat summarisation and automated investigation) from architecture specification to production, integrated with the AI platform layer.
• Applying binding AI security standards to every agent (tool-invocation control, identity binding and least-privilege scoping) and preparing handover packages for a managed service.
• Bachelor's degree in a relevant discipline, or equivalent professional experience.

Nice to have

• LangChain or LlamaIndex, vector databases, retrieval tuning and production Python.
• Agent observability, audit traceability and guardrails.
• AI red-teaming tools such as Garak or PyRIT.
• Agent frameworks such as LangGraph, AutoGen, Semantic Kernel or CrewAI.
• Prompt and agent evaluation tooling such as LangSmith, Promptfoo or equivalent.

Details

• Location: Bengaluru, Luxor North Tower, India.
• Role is one of seventeen across the UK, India and the US in the AI ML and Cloud Security function.