At a Glance
- Tasks: Build AI infrastructure and APIs for cutting-edge financial products.
- Company: Leading financial markets business focused on AI innovation.
- Benefits: Competitive salary up to £200,000, remote work options, and career growth.
- Other info: Exciting opportunity to work with advanced technologies in a dynamic environment.
- Why this job: Join a team at the forefront of AI and finance, making a real impact.
- Qualifications: Strong backend engineering skills in Python and experience with production systems.
The predicted salary is between 63000 - 77000 £ per year.
I’m working with a highly sophisticated financial markets business that is building a new generation of AI-powered products for institutional investors. They’re looking for an exceptional AI Platform Engineer to help turn LLM agents, quantitative models and complex datasets into reliable, production-grade products and workflows. This is not a research or prompt-engineering position. The focus is on building the infrastructure, APIs and backend systems that allow AI agents and models to operate reliably in production.
What you’ll own:
- Agent runtime infrastructure and orchestration
- Backend services and APIs connecting models, data and applications
- LLM and model endpoint integrations
- Authentication, permissions and security
- Logging, monitoring and observability
- Usage, latency, cost and error tracking
- Review workflows, audit trails and human-in-the-loop systems
- Internal AI tools used across research, markets and commercial teams
- Production reliability and scalability of the wider AI platform
What we’re looking for:
- You’ll ideally come from a strong backend/platform engineering background, with significant experience building production systems in Python.
- Key experience includes:
- Excellent Python engineering
- Strong API design — ideally FastAPI or similar
- Experience integrating LLMs / model APIs
- Agent frameworks, tool calling or model orchestration
- AWS, GCP or Azure
- Docker / Kubernetes
- Observability, logging and production monitoring
- Distributed or event-driven systems
- PostgreSQL, Redis, messaging or caching technologies
- Strong software engineering fundamentals
- You don’t need to be a frontend engineer, but enough React / TypeScript experience to contribute to internal tooling would be valuable.
- Experience within financial markets, quantitative finance, hedge funds or systematic trading would be highly relevant, although exceptional engineers from outside finance will absolutely be considered.
- Candidates with strong academic backgrounds, including PhDs in Computer Science, AI, Mathematics, Physics or related disciplines, are particularly interesting.
- This is a chance to work very close to the intersection of AI, software engineering and quantitative finance, building systems that are actively used rather than experimental prototypes.
Base salary up to £200,000 depending on experience. If your background sits somewhere between senior Python backend engineering, distributed systems and production AI/LLM infrastructure, I’d be very interested in speaking.
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