AI Engineer

• Strong experience in AI / Machine Learning Engineering (2-5 years)
• Hands-on experience building and deploying LLM-based systems
• Experience with Python and modern AI frameworks
• Strong understanding of model architecture, evaluation, and optimisation
• Experience working in a start-up or high-growth environment is highly beneficial
• Strong academic background - ideally from Oxford, Cambridge, UCL, Imperial or equivalent
• Ability to work in a fast-paced, high-performance engineering team

• £150,000 - £250,000 Salary (depending on experience)
• Join a well-funded AI start-up (£40M+ raised) at an early stage
• Work on real-world AI systems in production, not theory
• Direct access to founders and key decision-makers
• Opportunity to help shape product, architecture, and technical direction
• Work alongside top-tier engineers from elite academic and industry backgrounds
• Strong potential for equity and long-term upside
• Fast-moving, non-corporate, high-performance culture
• A genuine opportunity to be part of a category-defining AI company

We're working with a well-funded, high-growth AI start-up operating at the intersection of artificial intelligence and the legal sector, backed by over £40M in funding and scaling rapidly. They're now looking for an exceptional AI Engineer to join their core team and help build real, production-grade AI systems that are transforming how an entire industry operates. This is not a research-only role - it's about shipping real AI products. You'll be designing, building, and deploying systems using LLMs, agent frameworks, and modern AI infrastructure, working directly with founders and senior engineers in a fast-moving environment where your work has immediate impact. The team is made up of high-calibre engineers from top universities and leading tech companies, and they're looking for someone who can operate at that level. If you want to work on cutting-edge AI, move quickly, and be part of a company with genuine breakout potential - this is one of the most exciting opportunities on the market.