Senior, Forward Deployed Engineer (Physical AI & Self-Driving Labs)

About the job

Senior, Forward Deployed Engineer (Physical AI & Self-Driving Labs)

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 Physical AI capabilities to create self-driving labs and simulated tech transfers. You will work on orchestration of the physical space from the digital space. You will simulate the functioning of labs and a transfer to a line via virtual commissioning and Omniverse representations. This will support the ambitions of higher throughput and one-click deployment of a line. You will work hand in hand with the automation business and tech teams across R&D and manufacturing. You bring deep, hands-on AI/engineering expertise in Physical AI 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.

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 experience of full-stack or AI/ML engineering experience, including production deployments.

• Strong proficiency in Python and at least one of TypeScript/JavaScript, Go, or similar.

• Hands-on experience with GenAI patterns: agents, multi-agent orchestration, retrieval-augmented generation (RAG), prompt engineering, and evaluation.

• Strong experience in the physical space: labs, manufacturing control, edge deployment of models, predictive and anomaly detection modeling, closed-loop control.

• Strong experience in lab automation and self-driving lab workflows: robotics, instrument integration, and digital-to-physical orchestration that is aligned with the business platform and workflow (scheduling, execution and data capture).

• Strong experience in simulation of manufacturing lines and lab operations on physics-based or 3D simulation platforms such as NVIDIA Omniverse and Isaac Sim, applied to tech transfer, and with the NVIDIA physical AI and agentic model stack (Nemotron, etc.).

• 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 in regulated industries (pharma, healthcare, financial services) and familiarity with good practice regulations (GxP), General Data Protection Regulation (GDPR), and Sarbanes-Oxley (SOX).
• Experience with Manufacturing Execution Systems, Lab Execution Systems, etc.
• Experience extending lab automation into quality labs and manufacturing lines, working with automation, business and tech teams.
• Strong experience in computer vision systems, embedded systems and edge AI.
• 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 accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029.”

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