AI Engineer

We are a Specialist Digital Health Consultancy working with innovative organisations across healthcare, life sciences, and biotech to deliver intelligent, data-driven solutions that genuinely improve lives.

This role is ideal for an AI Engineer who wants to deepen their experience in Generative AI and applied machine learning, while working alongside senior engineers and architects on real, production-grade systems. You will not be siloed into a single product. Instead, you will gain exposure to a variety of client challenges, modern AI tooling, and best-in-class engineering practices.

If you are looking to move beyond experimentation and into well-engineered, scalable AI solutions, this is a strong next step. What You'll Be Doing

• Build Generative AI Solutions Develop and enhance GenAI applications using frameworks such as LangChain, LangGraph, or LlamaIndex, integrating with LLMs including GPT, Claude, and Gemini.

• Implement RAG Pipelines Support the design and delivery of Retrieval-Augmented Generation (RAG) solutions using vector databases such as Pinecone or Weaviate.

• Develop Production-Ready Services Write clean, maintainable code in Python and/or JavaScript, contributing to microservices and APIs that meet performance, security, and reliability standards.

• Work Cloud-First Deploy and support AI services within AWS, GCP, or Azure, using containerisation and CI/CD pipelines.

• Collaborate & Learn Work closely with Lead AI Engineers and Architects, contributing to design discussions, code reviews, and internal knowledge sharing.

• Apply AI-Assisted Engineering Responsibly Use tools such as GitHub Copilot, Cursor, or Claude Code to improve productivity while maintaining high engineering quality.

• AI & Engineering Experience Around 2-5 years' experience in software engineering, with at least 1-2 years working with AI/ML or Generative AI in a commercial setting.

• Solid Programming Foundations Strong skills in Python and/or JavaScript, with a good understanding of APIs, data handling, and software design principles.

• Cloud Awareness Experience deploying applications in AWS, GCP, or Azure, with some exposure to Docker and modern DevOps practices.

• Engineering Mindset An interest in clean code, testing, and maintainability, with a desire to build systems that scale beyond prototypes.

• Curiosity & Growth You enjoy learning, experimenting responsibly, and developing your skills in a fast-moving AI environment.

Nice to Have (But Not Essential)

• Experience with vector databases, embeddings, or prompt optimisation.
• Exposure to MLOps, model deployment, or monitoring tools.
• Background in data engineering, front-end development, or UX-aware AI applications.
• Interest or experience in healthcare or regulated industries.

• Salary package of £60,000-£90,000, depending on experience.
• Hybrid working with flexibility.
• Hands-on exposure to real-world AI systems, not just demos.
• Clear progression path towards Senior or Lead AI Engineer roles.
• Supportive, high-calibre engineering environment with strong mentorship.