Staff, Forward Deployed Engineer

About the Role: GSK’s Enterprise AI team builds AI solutions that prove value fast and scale to production. The Director, Forward Deployed Engineering leads the FDE function — the front of the Enterprise AI delivery pipeline that proves AI ideas with the business through PoCs, PoVs, MVPs and (where appropriate) first production versions, before handing proven solutions off to the Solutions Engineer for scale-up. The pattern is proven by AI-native companies — Anthropic, Palantir, OpenAI — and this role brings that model to GSK. This Staff role leads the Forward Deployed Engineering function with direct line management of the FDE team (Lead, Senior, and Forward Deployed Engineers, flat reporting structure). The Staff sets FDE strategy and engagement priorities, owns Director-level BU sponsor relationships, and represents Enterprise AI on FDE matters to GSK leadership. The role continues to contribute technically at the frontier of AI-augmented engineering — humans steer, agents execute. Why This Role Exists: Enterprise AI’s ability to build credibility with the business depends on engineers who can land inside BU problems, prove value quickly, and hand off cleanly. The Director, Forward Deployed Engineering builds and leads the function that makes this happen. Leads the FDE function — setting strategy, building the team, and owning the standards that determine whether the function delivers credibly. Owns the BU senior relationships that bring AI use cases to Enterprise AI and sustain engagement through the delivery cycle. Continues to contribute technically on the most strategic FDE engagements — keeping the Director’s judgement grounded in current AI engineering reality. Key Responsibilities: FDE Function Leadership: Lead the Forward Deployed Engineering function — strategy, structure, hiring, development, and standards. Hire, mentor, and develop the FDE team — creating development paths from G8 through to G5. Set the standards for AI-native engineering practice within the function — agent workflows, prompt and pattern libraries, handoff hygiene. BU Engagement & Strategic Delivery: Own relationships with Director and Senior Director-level BU sponsors across business units that bring AI use cases to Enterprise AI. Take on the most strategic FDE engagements personally — the ones that set precedents for the function. Make and defend portfolio-level kill/continue decisions across FDE engagements with BU and Enterprise AI leadership. Cross-Functional Leadership: Coordinate with the Solutions Engineering and Operations Engineering functions on the delivery pipeline; represent FDE in Enterprise AI leadership forums. Influence vendor strategy and tooling choices for AI-native engineering practice within Enterprise AI. Governance & Reporting: Ensure the FDE function operates within Code Orange, Responsible AI, and Accountability Report governance from the prototype stage onward. Provide regular reporting to Enterprise AI leadership on FDE function performance — engagement pipeline, outcomes, team development, and capacity. Required Functional Experience: At least 18+ years of experience in software engineering and AI/ML engineering, with significant time leading senior engineering teams or functions. Demonstrated experience taking AI ideas from sketch to working software at speed, in customer-facing engineering roles. Strong technical depth in GenAI patterns: agents, multi-agent orchestration, RAG, and evaluation. Daily use of AI coding agents (Claude Code, GitHub Copilot, Databricks AI Assistant) as the primary mode of development. Experience hiring, mentoring, and developing senior engineering talent. Track record of representing engineering functions to senior business stakeholders. Preferred Experience: Prior leadership experience at an AI-native company (Anthropic, Palantir, OpenAI, or similar) — Head of Forward Deployed Engineering, Director of Solutions, or equivalent. Experience in regulated industries (pharma, healthcare, financial services). Experience setting AI engineering standards at organisational scale. Education: Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience. Master’s degree/ Ph D in Computer Science, Mathematics or statistics or related field is advantageous. Skills Artificial Intelligence (AI), Artificial Intelligence Ethics, Artificial Neural Networks (ANNS), Classification Models, Deep Learning, Intelligent Automation (IA), Machine Learning (ML), Model Evaluation, Predictive Modeling, Python (Programming Language), Test Documentation Why GSK? Uniting science, technology and talent to get ahead of disease together. GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale. People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people. 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