Artificial Intelligence Engineer
π AI Engineer β Agentic Systems / Applied AI π
β¨ Series A AI Fintech Start-Up | Proven, repeat founders β¨
π London
πΈ Β£100k β Β£200k base (level dependent)
π² ~$160k equity vested over 4 years
π Onsite chef, barber, breakfast, gym membership
Iβm partnering with one of the most talked-about AI start-ups in London, currently disrupting the finance and investments markets. Having recently closed a record-breaking Series A they are now scaling a world-class AI engineering function.
You'll be building production-ready agentic AI systems for the investment and financial services markets, designed to handle complex, high-impact workflows for enterprise customers.
Youβll be working shoulder to shoulder with two of the most impressive founders in this market, directly contributing to the success and growth of the business at this early stage, working amongst the most exceptional peers in engineering and infra.
This suits high agency, high-performing individuals with an interest in owning part of the product and the growth of the company.
Youβll take responsibility for key parts of the AI stack, including:
- Architecting and deploying multi-agent systems
- Building scalable RAG pipelines and retrieval systems
- Creating evaluation frameworks (performance, safety, reliability)
- Shipping AI-driven products used in real-world enterprise settings
- Alongside this, youβll stay close to the engineering fundamentals β Python backend (FastAPI/Django), infrastructure, and production deployment.
Why people join environments like this:
β High talent bar across the team
β Direct access to founders and decision-makers
β Pace and exposure that accelerates your trajectory (12 months here wonβt feel like a typical year)
Background requred:
β Degree in a relevant discipline (Maths, Engineering, Computer Science, etc.)
β ~4+ years in AI/ML engineering, with strong software engineering foundation
β Experience taking agent-based systems into production
β Strong understanding of system design: orchestration, memory, deployment, monitoring
β Exposure to tools such as LangGraph, ReAct, CoT β or building similar systems from scratch
β Familiar with PyTorch / TensorFlow, RAG architectures, vector databases, modern cloud infra
β Experience in startup or consulting environments is a plus
β Comfortable working autonomously in fast-moving, sometimes ambiguous settings
With fresh funding and ambitious growth plans, this is a genuine scaling moment β and a chance to step into something high-impact early.
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