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

Gsk; England; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Hybrid work model

On-site in London/Stevenage

Job summary

GSK's Enterprise AI team builds AI solutions that prove value quickly and scale to production. The Forward Deployed Engineer is placed inside business unit teams to prototype, validate value, and hand off to the Sr. Solutions Engineer for scaling in the CMC area.

This UK-based hybrid role develops physical AI capabilities and orchestrates digital-to-physical workflows across R&D and manufacturing. You will work with AI/engineering experts to ship production-grade systems, mentor engineers, and

Qualifications

• Strong experience of full-stack or AI/ML engineering.
• Proficiency in Python and at least one of TypeScript/JavaScript, Go.
• Hands-on experience with GenAI patterns: agents, multi-agent orchestration, RAG, prompt engineering.
• Experience in lab automation, manufacturing control and edge AI.
• Familiarity with 3D simulation platforms like NVIDIA Omniverse and Isaac Sim.

Responsibilities

• Take ownership of high-priority BU use cases from problem framing to working prototype.
• Ship first production versions for clear paths to scale.
• Operate AI agent workflows for autonomous prototype delivery and validation.
• Embed with BU teams, prototype against real data and workflows.
• Package proven use cases for scale with architecture rationale and risks.
• Contribute reusable patterns to the organization’s pattern library.

Skills

AI/ML engineering

Python

JavaScript/TypeScript

Go

GenAI patterns

Edge deployment

NVIDIA Omniverse

Isaac Sim

Education

Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience

Master's degree in Computer Science or related field (advantageous)

Tools

NVIDIA Omniverse

Isaac Sim

GitHub Copilot

Claude Code

Databricks AI Assistant

Google Cloud Platform (GCP)

Microsoft Azure AI

Job description

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, and 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 sits 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 will 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 partnering 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

• 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.
• 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.
• 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, including working code, architecture rationale, open risks, and scaling concerns.
• 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:

• Strong experience of full-stack or AI/ML engineering, 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 modelling, closed-loop control.
• Strong experience in lab automation and self-driving lab workflows: robotics, instrument integration, and digital-to-physical orchestration 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.

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 minimum of 2/3 days a week onsite. Fully remote working is not available.

Locations

• HQ Central London or
• Stevenage. This role can be temporarily based at Stevenage. However, the Company plans to relocate its offices to Ware, UK, and the location of this role will 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.

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, Model Validation, Performance Optimizations, Software Development Life Cycle (SDLC)

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases, to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we are committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Equal Opportunity Employer

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at [e-mail] where you can also request a call.

Please note should your enquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive.