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

Description

The Enterprise AI team at the company builds AI products that prove their value quickly and then scale to production. Forward deployed engineers work with business unit teams to test AI ideas through proofs of concept, proofs of value and minimum viable products, usually over days to weeks. Proven solutions then pass to a Sr. Solutions Engineer for scale-up.

This senior role sits in the Chemical Manufacturing & Control area, which turns a validated molecule into a reliably made, quality-assured medicine. The area's current goal is to double New Product Introductions.

You will work inside the business, using AI coding assistants and multi-agent workflows for most of the routine coding, so your effort goes to framing problems, judgement and validation. The output is working software and a clear value case. Long-term operation of use cases is not your job, but you will work with the Sr. Solutions Engineer on the handover.

The work centres on document authoring and generation for the filing strategy that feeds a global single thread for regulatory filing documents. You will automate key regulatory documents with agents after a lean, AI-native redesign of the process, and help define an end-to-end knowledge system and agentic layer with the data analytics team and research technology partners. You will also mentor engineers around you.

The company is a global biopharma business whose purpose is to unite science, technology and talent to get ahead of disease.

Responsibilities

• Own high-priority business unit use cases from problem framing to a working prototype, typically within days to weeks, and reach a reasoned view on whether each should continue.
• Put the first production version of a use case live where the path is clear, before the Sr. Solutions Engineer takes it to scale.
• Run AI agent workflows for planning, coding, testing, review and documentation, choosing the right level of automation for each engagement.
• Build and direct prototype work with AI coding assistants, supplying judgement, course correction and validation.
• Design human-in-the-loop document authoring and review flows, including approval gates, inline subject matter expert feedback, confidence-based escalation and full audit trails for GxP and regulatory use.
• Build evaluation for agents and large language models: golden datasets, automated evals (including LLM-as-judge calibrated against expert review), regression tests and production monitoring for retrieval, generation and agent behaviour. Share the metrics with business unit and quality stakeholders.
• Work alongside business unit teams: attend standups, learn the domain, and prototype against real data and real workflows.
• Hand proven use cases to the Sr. Solutions Engineer with working code, architecture rationale, open risks and scaling concerns.
• Start Code Orange, Responsible AI and Accountability Report discussions during prototyping so the productionisation team does not inherit governance gaps.
• Add reusable agents, prompt templates and reference architectures to the organisation's pattern library after each engagement.
• Make and defend continue or stop recommendations at the end of each engagement, presenting them to business unit and Enterprise AI leadership.
• Coach business unit engineers on AI-augmented ways of working while embedded with them.

Requirements

• Strong full-stack or AI/ML engineering experience, including production deployments.
• Proven record of building and shipping production full-stack applications and APIs, from backend services to user interfaces.
• Strong Python, plus at least one of TypeScript/JavaScript, Go or a similar language.
• Hands-on work with GenAI patterns: retrieval-augmented generation, agents, document authoring and generation, human-in-the-loop review design, and agent/LLM evaluation including eval datasets, automated and expert-in-the-loop scoring, and regression testing.
• Experience with API integration, retrieval layers, knowledge graphs, ontologies or semantic search.
• Daily use of AI coding agents such as Claude Code, GitHub Copilot or Databricks AI Assistant as your main way of developing.
• Preferred: prior work as a Forward Deployed Engineer at an AI-native company (such as Anthropic, Palantir or OpenAI), or as a Customer Engineer or Solutions Architect at a hyperscaler.
• Preferred: experience with regulatory filing documents, such as Common Technical Document CMC sections, or other GxP documents, including authoring, review and validation workflows.
• Preferred: experience in regulated industries (pharma, healthcare or financial services), with familiarity with GxP, GDPR and Sarbanes-Oxley.
• Preferred: experience partnering with data analytics, data science or process science teams to turn analytical models into shared, reusable products.
• Preferred: track record of passing reusable engineering patterns to a wider team.
• Education: a Bachelor's degree in Computer Science, Software Engineering or equivalent practical experience. A Master's degree in Computer Science or a related field is an advantage.

Conditions

UK-based hybrid role with at least 2 to 3 days a week onsite. Fully remote working is not available.

Location is HQ Central London or Stevenage. Stevenage may be used on a temporary basis. The company plans to move its offices to Ware, UK, with the role's location changing to Ware in line with timelines set by the company, currently proposed for early 2029.

Closing date: 10th November 2026.

The company is an equal opportunity employer and welcomes candidates from all backgrounds.

Benefits

• Access to learning and development to build technical and leadership skills.
• A supportive team that values clear communication and practical problem solving.