[Hiring] Director, AI ML and Cloud Security @GSK

Role Description

Own all AI architecture for Cyber Architecture and Solutions — the designs that AI Engineering builds and a managed service vendor operates. You are the design authority for the agentic framework and the data fabric: nothing is built without a specification from your team. You lead three architects and carry architecture accountability across design, build and vendor operation.

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 Cyber Architecture and Solutions 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 a design authority role, not an AI governance role. You will personally own the agentic framework architecture — agent orchestration, tool invocation, identity binding, least-privilege scoping — and the data fabric design that determines what data flows where, at what classification, under what controls. Expect to whiteboard an agentic or RAG architecture you designed and defend the trade-offs. If your AI background is policy frameworks and vendor assessment rather than designs that were built, this will not suit you.

Responsibilities

• Act as design authority for every AI solution Cyber Architecture and Solutions builds; nothing enters engineering without a specification from this team.
• Own the agentic framework architecture: agent orchestration, tool invocation control, identity binding, least-privilege scoping, human-in-the-loop gates and trust boundaries.
• Own the data fabric architecture — what data flows where, at what classification, under what controls, and how the fabric evolves as the vendor introduces agentic capability.
• Own the AI reference design and pattern library that Engineering and the vendor build against.
• Lead three architects covering solution architecture, standards and governance.
• Chair the design authority board where every Cyber Architecture and Solutions AI build is approved or sent back before engineering capacity is allocated.
• Assess new AI tool proposals for architectural fit and reject what does not conform.
• Rule on feasibility for the highest-risk R&D and business AI proposals that AI Business Facing escalates to you.
• Assure vendor handover packages and retain architecture accountability once the vendor operates the solution.
• Set the architecture decision record template and arbitrate the decisions it captures, so design rationale stays traceable for audit and regulatory inspection.

Qualifications

• 12+ years of experience in cybersecurity or AI architecture, including experience leading technical teams across geographies, with expertise in AI architecture, including agentic frameworks, data fabric architecture, AI solution blueprints, and design authority for enterprise AI/ML solutions.
• Experience designing agentic frameworks, multi-agent systems, and Retrieval-Augmented Generation (RAG) architectures, including agent design patterns, trust models, orchestration, tool-calling boundaries, identity binding, least-privilege tool scoping, human-in-the-loop approvals, containment, kill switches, and rollback mechanisms.
• Experience designing data fabric architectures, including defining how data flows across systems, data classification requirements, applicable controls, and how these architectures evolve as agentic capabilities are introduced.
• Experience developing AI solution blueprints for security use cases, including GenAI alert triage, automated investigations, threat summarization, and AI-driven workflows, with experience establishing model and platform selection criteria across hosted and self-hosted LLMs, embeddings, vector stores, and orchestration platforms based on security, cost, latency, and data residency requirements.
• Experience incorporating AI security standards and threat modeling into solution design, including frameworks and standards such as the EU AI Act, NIST AI Risk Management Framework (AI RMF), and ISO/IEC 42001, and translating these requirements into technical specifications for engineering teams.

Preferred Qualification

• Working understanding of LangChain or LlamaIndex, vector databases, production Python and Kubernetes.
• AI use-case feasibility assessment and risk-based prioritisation before engineering build.
• Architecture quality review and standards governance.
• Regulated industry experience, including GxP and data integrity requirements applied to AI.
• North American AI architecture coverage and R&D pipeline engagement (US-based role).

Skills

• AI for Cybersecurity
• Application Security
• Cloud Security
• Computer Programming
• Data Security
• Identity Access Management (IAM)
• Information Systems
• Infrastructure Security
• ML Security
• Operating Systems Security
• Scripting
• Security Engineering
• Security Technologies
• Security Testing
• Vulnerability Management

Benefits

• Health care and other insurance benefits (for employee and family)
• Retirement benefits
• Paid holidays
• Vacation
• Paid caregiver/parental and medical leave