Technical Lead - Agentic AI

Location: Leeds (at least 1 day per week)

Company: One of the most exciting AI Product consultancies to hit the market in the last 12 months

Company X is growing fast, winning serious enterprise work, and building an in-house AI capability that moves quicker than the competition. With a raft of new projects ready to go in, we're looking for a Lead Engineer | Tech Lead to join the team.

We’re looking for innovators, the kind of engineer who doesn’t just read about new tools, but builds with them  you’ve got your own lab, side projects, half-finished experiments, or AI products you tinker with at night… keep reading.

• Lead and develop engineers, creating an environment of high trust, continuous improvement, and strong delivery outcomes
• Designing and building AI-first products for a diverse client base, from early-stage Health Tech startups to globally recognised automotive brands
• Shipping production-grade LLM-powered systems, including orchestration, agent frameworks, and conversational experiences that users actually rely on
• Owning the full product lifecycle, from early discovery and rapid prototyping through to scalable, enterprise-ready delivery
• Working at the intersection of product, engineering, and AI, translating real user problems into pragmatic technical solutions
• Embedding AI capability into products and teams, so value and knowledge stay inside the business rather than with external vendors

AND it would be even better if you can offer a mixture of the following:

• Experience in AI engineering, automation, workflow engineering, or software development, with real projects shipped to production
• Hands-on experience building AI-powered products, not just prototypes, from orchestration to deployment
• Experience leading/mentoring a small team of engineers
• A mindset rooted in good engineering practice: continuous improvement, pragmatic governance, and coaching-led leadership
• Commercial experience with the Microsoft eco-system i.e. .NET, Azure, Fabric
• Strong exposure to LLMs such as Claude, Codex, Gemini, or open-source models
• Experience with LLM orchestration frameworks and agent-based systems (e.g. Lang Chain, Llama Index, Auto Gen, custom agent frameworks)
• Familiarity with prompt engineering, tool calling, retrieval-augmented generation (RAG), and multi-agent workflows
• Experience integrating AI into real systems, APIs, event-driven architectures, data pipelines, and automation platforms (e.g. UiPath, Blue Prism)
• Comfortable experimenting with new models, SDKs, and platforms, and evaluating what’s production-ready vs hype