About the role
Lead Forward Deployed Engineer
AI / Product / Consulting
Location:
Hybrid Job Type:
Full-time Level:
Lead / Principal
Individual Contributor The Opportunity
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 would suit an experienced engineer who is operating at the forefront of AI development and is equally comfortable writing production code, challenging a product strategy, presenting to senior stakeholders and working directly with clients. How You'll Work
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. You'll: Lead discovery with business and technical stakeholders.
Separate the problem a client describes from the underlying problem they actually need to solve.
Structure ambiguity into clear hypotheses, options, trade-offs and recommendations.
Develop business cases around value, cost, adoption risk and expected outcomes.
Communicate effectively with both technical and executive audiences.
Decide
Take ownership of what should be built
and what shouldn't. You'll: Translate product discovery into a focused, outcome-driven roadmap.
Own scope, priorities, sequencing and trade-offs.
Create clear product documentation including problem briefs, PRDs, user stories and acceptance criteria.
Define and track meaningful success metrics.
Work closely with UX and design teams to ensure solutions are built around genuine user needs.
Run agile delivery processes, including backlogs, sprints, demos and releases.
Continue to own and iterate on products after launch based on user feedback and performance data.
Build & Deploy
When the problem is defined, you'll get hands-on and build. You'll: Build production-quality software using
Python and/or TypeScript .
Develop full-stack applications, APIs, AI agents and workflows.
Work with technologies including
Next.js, React, FastAPI, Fastify, FastMCP and Hono .
Design and implement agentic applications using technologies such as
LangGraph, AutoGen, Claude Agent SDK, OpenAI tooling or custom orchestration frameworks .
Integrate leading and self-hosted LLMs with tools, data and external systems using
MCP and custom connectors .
Implement RAG solutions using vector databases and hybrid retrieval where appropriate.
Work across relational, document, key-value and graph databases depending on the problem.
Develop prompt and context engineering approaches focused on accuracy, reliability, cost and latency.
Make structured use of AI-assisted development tools such as
Claude Code, Cursor, GitHub Copilot and Codex .
Fine-tune or adapt models where there is a genuine use case.
Production & Engineering
You'll own solutions all the way into production, including: Infrastructure and deployment.
AI evaluation and testing frameworks.
MCP server implementation.
Cloud deployment across
AWS, Azure, Cloudflare or Vercel .
Docker, Kubernetes and/or serverless architectures.
TDD and robust software engineering practices.
Security, secrets management and SAST/DAST.
Structured logging, monitoring, metrics and tracing.
Automated CI/CD using tools such as
GitHub Actions or Jenkins .
Performance, scalability and cost optimisation.
Operational ownership of the systems you build.
Leadership & Mentoring
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.
Set the technical and product standard on client engagements.
Review work, raise engineering standards and unblock teams.
Contribute to reusable accelerators, playbooks and technical assets.
Help interview, onboard and develop future team members.
What We're Looking For
Engineering
6+ years' experience
building production software.
At least
3 years' experience building production applications using AI and/or agentic development approaches .
Strong hands-on experience building agents and multi-step AI workflows
not simply integrating chat or prompted models.
Experience with agent frameworks such as
LangGraph, AutoGen, Claude Agent SDK, OpenAI tooling
or equivalent.
Strong
Python and/or TypeScript
experience.
Strong understanding of OOP, SOLID, 12-factor application development and microservice architecture.
Experience building applications with frameworks such as
Next.js and FastAPI
or equivalent.
Experience with vector databases, retrieval pipelines and AI evaluation frameworks.
Cloud-native deployment experience with at least one of
AWS, Azure, Cloudflare or Vercel .
Experience with Docker, Kubernetes and CI/CD tooling.
A deep understanding of how LLMs behave, where they fail and how to optimise accuracy, latency and cost.
A demonstrable track record of actually building and shipping technology
GitHub projects, portfolios, side projects, open-source contributions or similar.
Product
You should also be comfortable taking ownership beyond the engineering implementation. We're looking for experience with: Owning a product or significant product area from discovery through delivery.
Product discovery and problem framing.
Roadmapping, prioritisation and opportunity assessment.
Writing PRDs, user stories and acceptance criteria.
Defining and measuring product success metrics.
Using data and evidence to change product direction.
Working closely with UX and design teams.
Running agile delivery processes with accountability for outcomes rather than simply participating in ceremonies.
Consulting & Client Leadership
This is a highly client-facing position, so you'll need: Previous experience in
consulting, professional services, forward deployment or another client-facing environment .
Experience owning client relationships rather than simply attending client meetings.
The ability to structure ambiguous problems and make clear recommendations to senior, non-technical stakeholders.
Excellent written communication, including decision papers, proposals and executive readouts.
Experience with scoping, estimation, change control and stakeholder management.
The confidence to challenge a client or senior stakeholder constructively when the evidence supports a different approach.
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
The following would be advantageous: 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.
Public technical writing, conference talks or other thought leadership around AI.
AWS Professional certification or another relevant industry certification.
What Success Looks Like
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. First 6 months: You'll have defined and delivered a meaningful product increment that has improved a client-relevant metric and demonstrated enough value to support further investment. 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.
The opportunity to work at the forefront of
AI, agentic development and digital health .
Significant autonomy and ownership over the solutions you build.
Opportunities for technical leadership, mentoring and career development.
A supportive environment focused on continuous learning.
Competitive salary and benefits.
The opportunity to work on technology with meaningful real-world impact.
Interested?
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.
TPBN1_UKTJ
AI / Product / Consulting
Location:
Hybrid Job Type:
Full-time Level:
Lead / Principal
Individual Contributor The Opportunity
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 would suit an experienced engineer who is operating at the forefront of AI development and is equally comfortable writing production code, challenging a product strategy, presenting to senior stakeholders and working directly with clients. How You'll Work
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. You'll: Lead discovery with business and technical stakeholders.
Separate the problem a client describes from the underlying problem they actually need to solve.
Structure ambiguity into clear hypotheses, options, trade-offs and recommendations.
Develop business cases around value, cost, adoption risk and expected outcomes.
Communicate effectively with both technical and executive audiences.
Decide
Take ownership of what should be built
and what shouldn't. You'll: Translate product discovery into a focused, outcome-driven roadmap.
Own scope, priorities, sequencing and trade-offs.
Create clear product documentation including problem briefs, PRDs, user stories and acceptance criteria.
Define and track meaningful success metrics.
Work closely with UX and design teams to ensure solutions are built around genuine user needs.
Run agile delivery processes, including backlogs, sprints, demos and releases.
Continue to own and iterate on products after launch based on user feedback and performance data.
Build & Deploy
When the problem is defined, you'll get hands-on and build. You'll: Build production-quality software using
Python and/or TypeScript .
Develop full-stack applications, APIs, AI agents and workflows.
Work with technologies including
Next.js, React, FastAPI, Fastify, FastMCP and Hono .
Design and implement agentic applications using technologies such as
LangGraph, AutoGen, Claude Agent SDK, OpenAI tooling or custom orchestration frameworks .
Integrate leading and self-hosted LLMs with tools, data and external systems using
MCP and custom connectors .
Implement RAG solutions using vector databases and hybrid retrieval where appropriate.
Work across relational, document, key-value and graph databases depending on the problem.
Develop prompt and context engineering approaches focused on accuracy, reliability, cost and latency.
Make structured use of AI-assisted development tools such as
Claude Code, Cursor, GitHub Copilot and Codex .
Fine-tune or adapt models where there is a genuine use case.
Production & Engineering
You'll own solutions all the way into production, including: Infrastructure and deployment.
AI evaluation and testing frameworks.
MCP server implementation.
Cloud deployment across
AWS, Azure, Cloudflare or Vercel .
Docker, Kubernetes and/or serverless architectures.
TDD and robust software engineering practices.
Security, secrets management and SAST/DAST.
Structured logging, monitoring, metrics and tracing.
Automated CI/CD using tools such as
GitHub Actions or Jenkins .
Performance, scalability and cost optimisation.
Operational ownership of the systems you build.
Leadership & Mentoring
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.
Set the technical and product standard on client engagements.
Review work, raise engineering standards and unblock teams.
Contribute to reusable accelerators, playbooks and technical assets.
Help interview, onboard and develop future team members.
What We're Looking For
Engineering
6+ years' experience
building production software.
At least
3 years' experience building production applications using AI and/or agentic development approaches .
Strong hands-on experience building agents and multi-step AI workflows
not simply integrating chat or prompted models.
Experience with agent frameworks such as
LangGraph, AutoGen, Claude Agent SDK, OpenAI tooling
or equivalent.
Strong
Python and/or TypeScript
experience.
Strong understanding of OOP, SOLID, 12-factor application development and microservice architecture.
Experience building applications with frameworks such as
Next.js and FastAPI
or equivalent.
Experience with vector databases, retrieval pipelines and AI evaluation frameworks.
Cloud-native deployment experience with at least one of
AWS, Azure, Cloudflare or Vercel .
Experience with Docker, Kubernetes and CI/CD tooling.
A deep understanding of how LLMs behave, where they fail and how to optimise accuracy, latency and cost.
A demonstrable track record of actually building and shipping technology
GitHub projects, portfolios, side projects, open-source contributions or similar.
Product
You should also be comfortable taking ownership beyond the engineering implementation. We're looking for experience with: Owning a product or significant product area from discovery through delivery.
Product discovery and problem framing.
Roadmapping, prioritisation and opportunity assessment.
Writing PRDs, user stories and acceptance criteria.
Defining and measuring product success metrics.
Using data and evidence to change product direction.
Working closely with UX and design teams.
Running agile delivery processes with accountability for outcomes rather than simply participating in ceremonies.
Consulting & Client Leadership
This is a highly client-facing position, so you'll need: Previous experience in
consulting, professional services, forward deployment or another client-facing environment .
Experience owning client relationships rather than simply attending client meetings.
The ability to structure ambiguous problems and make clear recommendations to senior, non-technical stakeholders.
Excellent written communication, including decision papers, proposals and executive readouts.
Experience with scoping, estimation, change control and stakeholder management.
The confidence to challenge a client or senior stakeholder constructively when the evidence supports a different approach.
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
The following would be advantageous: 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.
Public technical writing, conference talks or other thought leadership around AI.
AWS Professional certification or another relevant industry certification.
What Success Looks Like
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. First 6 months: You'll have defined and delivered a meaningful product increment that has improved a client-relevant metric and demonstrated enough value to support further investment. 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.
The opportunity to work at the forefront of
AI, agentic development and digital health .
Significant autonomy and ownership over the solutions you build.
Opportunities for technical leadership, mentoring and career development.
A supportive environment focused on continuous learning.
Competitive salary and benefits.
The opportunity to work on technology with meaningful real-world impact.
Interested?
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.
TPBN1_UKTJ
About this listing
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