Staff Solution Support Engineer

About the Role GSK's Enterprise AI team is building an integration and operations capability that turns AI potential into enterprise-grade, production-ready deployment. The Staff Solutions Engineer leads the Solutions Engineering function — the architectural and engineering backbone that bridges AI capability and enterprise systems at scale, and keeps AI products healthy, governed, and improving after go-live. As the Staff Support Solutions Engineer, you will lead the Solutions Engineering function within Enterprise AI, setting the architectural strategy, developing the team, and personally leading the highest-stakes integration programmes. This is a hands-on technical leadership role: you will design, build, and review AI systems yourself — including LLM, agentic, and retrieval-based solutions — and set the engineering bar for the function. Where the Senior Solutions Engineer owns complex individual engagements, the Staff operates at the portfolio level — ensuring integration patterns are reusable, architectural standards are consistent, every AI product is managed through a clear lifecycle, and the function scales to meet the demands of a rapidly maturing AI portfolio. You will also own the vision for Intelligent Operations in Enterprise AI: the observability, automation, and AI-assisted operating model that lets a growing portfolio of AI products run reliably, safely, and cost-effectively at scale. The role carries direct accountability for production. Expect to spend roughly 40% of your time owning production operations and support — keeping the lights on (KTLO), meeting SLAs and service metrics, and managing strategic supplier delivery — and roughly 60% on engineering, with a deliberate focus on using that engineering to automate operations and steadily reduce the operational load. You will direct a fleet of AI agents and Senior Solutions Engineers to continuously improve the cost at which value is delivered. As applications scale in deployment, you are responsible for identifying when the current engineered solution needs to be refactored and/or optimized, and for leading that change. Why This Role Exists As the Enterprise AI portfolio scales, the complexity of integration and operations grows faster than individual Senior Solutions Engineers can absorb. A Staff-level leader is needed to: Raise the architectural ceiling across the portfolio by converting individual engagement experience into reusable patterns and standards that reduce cost and risk at scale. Lead the most novel and precedent-setting integrations — those involving architectural territory the function has not navigated before — and stay close enough to the code to make authoritative engineering decisions. Establish Product Lifecycle Management (PLM) for Enterprise AI, so every AI product and model is governed consistently from ideation through scale, operation, and retirement.