Senior, Forward Deployed / Full Stack Engineer (Document Authoring & Knowledge Systems)

Job description

Senior, Forward Deployed / Full Stack Engineer (Document Authoring & Knowledge Systems) About GSK Enterprise AI Enterprise AI is GSK’s centre of gravity for applied artificial intelligence. We pair forward deployed engineers and full-stack engineers with scientific, clinical, and business teams to build AI products that get used — not pilots that get archived. We work fast, ship in production, and measure ourselves on outcomes that matter to patients. GSK is a global biopharma company with a purpose to unite science, technology, and talent to get ahead of disease together. We are committed to building a diverse and inclusive team — we welcome candidates from all backgrounds and underrepresented groups in technology, science, and pharma. Position Summary GSK’s Enterprise AI team builds AI solutions that prove value fast and scale to production. The Forward Deployed Engineer (FDE) is the engineer GSK sends in to find out whether an AI idea will work — embedded with business unit (BU) teams, proving ideas through proofs of concept (PoCs), proofs of value (PoVs), and minimum viable products (MVPs) at a days-to-weeks cadence, then handing the proven solution off to the Sr. 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 specific role sites in the Chemical Manufacturing & Control (CMC) area. This is the GSK function that turns a validated molecule into a reliably manufactured, quality-assured medicine; its mission is to get safe, effective, consistently manufactured medicines to patients, faster. Its current mission is to double New Product Introductions (NPIs). As a Senior Forward Deployed Engineer, you’ll be embedded in a team shaping how AI transforms GSK’s process development around the world. Most prototyping work is AI-augmented: AI coding assistants and multi-agent workflows handle the bulk of routine coding, freeing the FDE to focus on framing, judgement, and validation. The role works directly inside the customer’s business and emerges with working software and a defensible value hypothesis, not slideware. The FDE does not carry use cases through to long-term operations and partner with the Sr. Solutions Engineer is part of the role. This role will build the document authoring and generation capabilities to foster our filing strategy that feed a global single thread for regulatory filing documents. You will work on key regulatory documents and automate as much of the work as possible with agents after a lean, AI-native redesign of the business process. You will also need to define an end-to-end knowledge system. You will work hand in hand with the data analytics team & Tech partners in research to define the knowledge system, the agentic layer across the enterprise. You bring deep, hands-on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you. Key Responsibilities This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following: PoC / PoV / MVP Delivery Take ownership of high-priority BU use cases from problem framing through to a working prototype, at days-to-weeks cadence, and form a defensible view on whether each should progress. Ship first production versions directly for use cases where the path is clear — before the Sr. Solutions Engineer takes them forward to scale. AI-Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery — selecting the right level of automation for each engagement. Use AI coding assistants as the default mode of building; provide judgement, course correction, and validation. Design human-in-the-loop workflows for document authoring and review — approval gates, inline SME review and feedback capture, confidence-based escalation, and full audit trails suitable for good practice regulations (GxP) and regulatory use. Build agent and large language model (LLM) evaluation — curated golden datasets, automated evals (including LLM-as-judge calibrated against expert review), regression testing and production monitoring for retrieval, generation and agent behaviour, with metrics shared with BU and quality stakeholders. Customer Embedding & Handoff Embed with BU teams — attend standups, understand the domain, prototype against real data and real workflows. Package proven use cases cleanly for the Sr. Solutions Engineer — working code, architecture rationale, open risks, and scaling concerns. Governance, Standards & Coaching Begin Code Orange, Responsible AI, and Accountability Report conversations during prototyping — so the productionisation team does not inherit governance debt. Contribute reusable agents, prompt templates, and reference architectures to the organisation’s pattern library after each engagement. Form and defend kill/continue recommendations at the end of each engagement — presenting clearly to BU and Enterprise AI leadership. Coach BU engineers on AI-augmented ways of working while embedded, building BU capability alongside delivery outcomes. Why You! We are seeking professionals with the following required skills and qualifications to help us achieve our goals: Strong full-stack or AI/ML engineering experience, including production deployments. Demonstrated ability to build and ship production full-stack applications and APIs, from backend services to user interfaces. Strong proficiency in Python and at least one of TypeScript/JavaScript, Go, or similar. Hands-on experience with GenAI patterns: retrieval-augmented generation (RAG), agents, document authoring and generation, human-in-the-loop review design, and agent/LLM evaluation (eval datasets, automated and expert-in-the-loop scoring, regression testing). Experience with API integration, retrieval layers, knowledge graphs, ontologies, or semantic search. Daily use of AI coding agents (Claude Code, GitHub Copilot, Databricks AI Assistant) as the primary mode of development. Preferred Experience Prior experience as a Forward Deployed Engineer at an AI-native company (Anthropic, Palantir, OpenAI, or similar), or as a Customer Engineer / Solutions Architect at a hyperscaler. Experience with regulatory filing documents (e.g. Common Technical Document (CTD) CMC sections) or other GxP documents, and with document authoring, review and validation workflows. Experience in regulated industries (pharma, healthcare, financial services) and familiarity with GxP, General Data Protection Regulation (GDPR), and Sarbanes-Oxley (SOX). Experience partnering with data analytics, data science, or process science teams to turn analytical models into shared, reusable products. Track record of contributing reusable engineering patterns back to a broader team. Education Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience. Master’s degree in Computer Science or related field is advantageous. Ready to apply? If this role excites you and matches your experience, we would love to hear from you. Please submit your application and a short note telling us why you want to join and what you would bring to this role. We look forward to hearing from you. If you need adjustments during the process, tell us and we will support you. (Please take a personal copy of the Job Description, as this will not be available online post closure of the advert) Closing Date:   10th November 2026 Working Pattern This is a UK based hybrid role, with a min of 2/3 days a week onsite. Fully remote working is not available. Locations: 1) HQ Central London or 2) Stevenage - This role can be temporarily be based at Stevenage location. However, the Company plans to relocate its offices to Ware, UK. The location of this role will therefore subsequently change to Ware, UK in a