Description
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.
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.
Key Responsibilities:
Function Leadership & Team Development:
- Lead the Solutions Engineering function , strategy, team structure, hiring, development, and standards.
- Hire, mentor, and develop Senior Solutions Engineers, building clear development paths with active coaching and regular feedback.
- Set the architectural and AI engineering standards and integration patterns the whole function operates to, ensuring consistency and quality across all engagements.
Hands-On AI and Product Engineering:
- Dedicate the majority of your time to engineering, with a primary focus on building automation, tooling, and AI-assisted capabilities that reduce manual operations and improve reliability of the production portfolio.
- Personally design, build, and ship production AI solutions , including LLM-based applications, agentic workflows, retrieval-augmented generation (RAG), and ML model serving , integrated with GSK enterprise systems.
Portfolio Architecture & Standards:
- Own the architectural strategy for AI integration across the Enterprise AI portfolio , defining where the function is heading and what standards it operates to.
- Define and maintain canonical integration patterns, architecture decision records, and design standards that enable faster, lower-risk delivery across all engagements.
Product Lifecycle Management (PLM) for Enterprise AI:
- Establish stage gates and release criteria , covering evaluation results, security, data privacy, regulatory and quality requirements , that balance speed with enterprise and regulatory risk.
- Maintain a portfolio-level inventory of AI products, models, versions, dependencies, owners, and lifecycle status, with clear processes for change management, deprecation, and retirement.
Intelligent Operations for Enterprise AI:
- Design and deliver the Intelligent Operations model for the Enterprise AI organisation: end-to-end observability, automated incident detection and response, and continuous improvement of deployed AI products.
Intelligent Operations & Support:
- Own production operation and support for Enterprise AI products and integrations, including KTLO (keep-the-lights-on) activities such as patching, upgrades, dependency and certificate management, capacity, and break-fix.
Agent-Led Delivery, Cost-to-Value & Solution Evolution:
- Direct a fleet of AI agents and Senior Solutions Engineers , setting objectives, guardrails, and review standards , to continuously improve the cost at which value is delivered across the Enterprise AI portfolio.
Strategic Delivery:
- Take personal ownership of the highest-stakes integrations , those that set precedents for the function, involve novel architectural territory, or carry significant enterprise risk.
Cross-Functional Influence & Partner Engagement:
- Represent the Solutions Engineering function in Enterprise AI leadership forums, shaping cross-function delivery standards and platform strategy.