Software Engineer (AI)

TL;DR

Software Engineer (AI) (AI Engineering): Building and integrating AI-powered features such as LLM-driven services and RAG pipelines into production-grade systems with an accent on scalability and backend reliability. Focus on developing agent-based workflows, optimizing system performance, and embedding AI-native capabilities into core products.

Location: Hybrid in Leeds, UK

Salary: £70,000 - £110,000 per annum

Company

A technology-led organisation building a genuinely AI-native capability by embedding artificial intelligence into its products and long-term strategy.

What you will do

• Design, build, and maintain scalable backend systems and services.
• Develop and evolve a production-grade AI platform.
• Integrate AI-powered features including LLM-driven services, RAG pipelines, and agent-based workflows into core systems.
• Leverage AI-assisted engineering workflows using tools like GitHub Copilot, Claude Code, or Cursor.
• Apply modern software engineering best practices including clean code, testing, CI/CD, and observability.
• Collaborate with product, data, and platform teams to deliver high-quality features.

Requirements

• Strong experience building and maintaining production systems.
• Solid understanding of system design, scalability, and performance considerations.
• Proficiency in at least two modern programming languages and experience developing backend APIs.
• Exposure to Large Language Models (LLMs), API integrations, or prompt-based workflows.
• Experience with version control and CI/CD pipelines.
• Must be based in or able to work in a hybrid model in Leeds, UK.

Nice to have

• Experience with Retrieval-Augmented Generation (RAG), vector databases, or embeddings.
• Experience with cloud platforms, preferably AWS.
• Familiarity with emerging AI tooling such as MCP, A2A, or Threads.
• Open-source contributions or side projects involving AI or scalable systems.

Culture & Benefits

• Hybrid working model with remote flexibility.
• Private healthcare.
• Funded professional development and learning opportunities.
• Opportunity to work on modern, AI-enabled systems at scale.
• Clear progression paths within a growing engineering function.