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

GSK; Greater London; Híbrido; GBP 90.000 - 150.000; Jornada completa

Descripción de la vacante

GSK Enterprise AI in the United Kingdom seeks a Senior Forward Deployed Engineer to embed with business units and deliver AI-enabled document authoring and knowledge systems. You will build production-grade full-stack solutions, lead PoCs and MVPs, and drive governance for responsible AI practices.

As a senior engineer, you will work hybrid in the UK, shaping AI transformations across CMC workflows, regulatory filing documents, and knowledge systems.

Formación

• Bachelor's degree in Computer Science, Software Engineering, or related field.
• Master's degree advantageous.
• Experience building production full-stack apps and APIs.

Responsabilidades

• PoC/PoV/MVP delivery for high-priority BU use cases within a days-to-weeks cadence.
• AI-native engineering: plan, code, test, review autonomous prototypes and validate outcomes.
• Customer embedding: prototype with BU teams and hand off to Sr. Solutions Engineer with clear arch rationale.
• Governance, standards & coaching: contribute reusable patterns and govern prototype governance and risk.

Conocimientos

Full-stack engineering

AI/ML engineering

Production deployments

Python

JavaScript/TypeScript

GenAI patterns

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Claude Code

GitHub Copilot

Databricks AI Assistant

Descripción del empleo

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

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.

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. 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 accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029.

#AGTech

#LI-Hybrid

What we value

You are practical, inclusive and open to feedback. You bring technical understanding and strong empathy for users. You work in active voice and keep communication simple. You support colleagues and help teams make confident, evidence-based decisions. You want to grow your product and security skills while delivering outcomes that matter.

What you will gain

You will join a supportive team that values clear communication and practical problem solving. You will have access to learning and development to grow both technical and leadership skills. Your work will support technology that enables critical work across the company and helps improve healthcare outcomes.

Skills

AI Frameworks, Algorithm Optimization, Artificial Neural Networks (ANNS), Computer Programming, Deep Learning, Feature Engineering, Google Cloud Platform (GCP) for Machine Learning, Machine Learning Algorithms, Machine Learning Operations, Microsoft Azure Data and AI, ML Frameworks, Model Evaluation, Model Training