Forward Deployed Engineer

We're working with an innovative, global digital health technology business that partners with major organisations across the pharmaceutical, biotech and healthcare sectors. They are looking for a Lead Forward Deployed Engineer who can operate across three disciplines that are often split between different roles: consulting, product leadership and hands-on engineering. You'll work directly with clients to understand complex business and technical challenges, determine what is worth building, and then personally take solutions from idea through to production. This is not a traditional engineering role where you'll receive a fully defined backlog and focus solely on implementation. You'll be expected to shape the problem, make product decisions, build the solution and own the outcome.

The role is built around three core areas:

• Shape: Work with business and technical leaders to turn ambiguous problems into clear, valuable and buildable opportunities.
• Decide: Take ownership of what should be built and what shouldn't.
• Build & Deploy: When the problem is defined, you'll get hands-on and build.

You'll own solutions all the way into production, including infrastructure and deployment, AI evaluation and testing frameworks, cloud deployment across AWS, Azure, Cloudflare or Vercel, and automated CI/CD using tools such as GitHub Actions or Jenkins.

Although this is an individual contributor role, you'll have significant influence across projects and teams. You'll mentor engineers in AI engineering, system design, product thinking and agentic architectures.

What We're Looking For

• Engineering: 6+ years' experience building production software, strong hands-on experience building agents and multi-step AI workflows, and experience with agent frameworks such as LangGraph, AutoGen, Claude Agent SDK, OpenAI tooling or equivalent.
• Product: Experience owning a product or significant product area from discovery through delivery, writing PRDs, user stories and acceptance criteria, and defining and measuring product success metrics.
• Consulting & Client Leadership: Previous experience in consulting, professional services, forward deployment or another client-facing environment, and the ability to structure ambiguous problems and make clear recommendations to senior, non-technical stakeholders.

Other Requirements: A strong commitment to clean code, testing, security, observability, scalability, performance and cost efficiency. Excellent communication and written skills. A founder-style mindset and enthusiasm for solving ambiguous, high-impact technical and commercial problems. Willingness to travel to client sites when required. Bachelor's or Master's degree in Computer Science, Machine Learning or a related technical discipline.

Desirable Experience: Experience within healthcare, life sciences, pharmaceuticals or biotech, including clinical, commercial, regulatory or R&D environments. Background within a leading consultancy, product-led technology company or high-growth startup.

What Success Looks Like: In the first 90 days, you'll be expected to take ownership of a client relationship, lead a discovery process and have working software in front of real users. In the first year, you'll be helping set the standard for how AI products are delivered, mentoring others and contributing to reusable technology, processes and accelerators.

What You'll Get: Hybrid working with exposure to high-profile clients and complex technology challenges, a collaborative, people-focused culture, and competitive salary and benefits.

If you're an experienced engineer who wants to combine hands-on AI engineering, product ownership and client leadership, this is an opportunity to have genuine ownership from problem definition through to production. Apply now with your CV to be considered.