Associate Director - AI ML and Cloud Security - AI Agent Engineering
GSK (company site, opens in a new tab)15+ yrsBengaluruOn-siteDirect career pageEst. 45–85 LPA
Posted 3d ago
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Job description
Structured overview of role & requirements
About This Role
- Own and lead development of the agent layer in the agentic framework, specifically the agent development pipeline including LLM integration, prompt-to-action engineering, agent evaluation and testing, and reusable agent components.
- Build GenAI security use cases such as alert triage automation and threat summarisation and ensure binding AI security standards are applied to every agent including managing AI security sign-off before release.
- Lead a small team of agent engineers with hands-on coding, mentor them, manage the agent workstream handover to managed service, and partner with AI Platform Engineering to maintain service level for model endpoints and token budgets.
Minimum Requirements
- 15+ years in cyber security or AI engineering in a regulated environment with focus on AI Agent Engineering (agent layer of the agentic framework) and hands-on leadership of an agent engineering team (build, not design).
- In-depth knowledge of agent engineering including LLM integration, prompt-to-action engineering, multi-agent orchestration, tool/function calling, memory/state management, retrieval-augmented generation, prompt and model version control, and reusable components.
- Experience building GenAI security use cases from architecture to production, including alert triage automation and threat summarisation, and applying AI security standards such as tool-invocation control, identity binding, least-privilege scoping.
- Bachelor's degree in relevant discipline or equivalent professional experience.
Ideal Candidate Profile
- Experienced leader comfortable balancing hands-on engineering with team leadership in AI agent development for production environments, not just proof-of-concept.
- Demonstrated expertise in agent evaluation and testing methodologies for non-deterministic outputs in a regulated setting, with ability to implement agent safety engineering practices.
- Skilled in working to defined AI architecture specifications and security standards while escalating design issues, and experienced in preparing operational handover documentation for managed service teams.