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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - **Company:** Markit - **Location:** Avon, UK - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, Cursor (Graphical User Interface Elements), Github, Graph Database, Python (Programming Language), Key Management, Machine Learning, Object-Oriented Software Development, Next.js, Software Engineering, Systems Integration, TypeScript, Data Logging, GitHub Copilot, Power Platform Integration, ReactJS, Large Language Models, Multi-Agent Systems, Software Application Programming, Fastapi, Kubernetes, Information Technology, Production Code, Cloudflare, Automation Anywhere, Serverless Computing, Docker, Jenkins, Static Application Security Testing, Microservices, Dynamic Application Security Testing - **Published:** August 17, 2026 - **Apply:** https://www.totaljobs.com/job/forward-deployed-engineer/markit-placements-job107858685 ## About the Role * 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., * 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., 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. ## Description 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., * 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. ## Related Videos - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [The Intent Engineer: Closing the Gap Between Business & Engineering - Manuel Klein](https://www.wearedevelopers.com/videos/1855-the-intent-engineer-closing-the-gap-between-business-engineering-manuel-klein) - [Our GitOps approach for deploying an Identity Provider and an API Gateway in a SaaS company](https://www.wearedevelopers.com/videos/776-our-gitops-approach-for-deploying-an-identity-provider-and-an-api-gateway-in-a-saas-company) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer)