Applied AI Engineer
On-siteLondon, England, United Kingdom
Job Summary
Develop and maintain Python-based AI applications, building production-ready Agentic AI/LLM systems that automate complex commodity trading workflows. Debug model performance issues, handle edge cases, and optimize system reliability while implementing monitoring for AI/ML systems. Build document workflows using LLMs and classical NLP, rapidly prototype new features, and implement them to production. Write comprehensive tests and participate in code reviews, technical design discussions, and architecture decisions. Communicate effectively with technical and non-technical stakeholders to translate business requirements into production code. Support the Data Science & Engineering teams as a Centre of Excellence for Agentic AI, providing knowledge sharing and tool adoption across global operations.
Required Qualifications
- 5-8+ years of experience building production AI/ML systems
- Modern Python proficiency with deep knowledge of the ecosystem (Pydantic, FastAPI, asyncio, type safety)
- Experience with modern AI frameworks (we currently favour Pydantic AI)
- Production experience maintaining human-in-the-loop systems and AI monitoring/observability
- Strong fundamentals in AI/ML evaluation frameworks
- Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails
- In depth understanding of modern software design principles (e.g. microservices, event-driven architectures, domain driven design, object oriented programming, test driven development)
- In depth understanding of modern software development lifecycle (CI/CD, IaC, Containerisation)
- Practical experience with cloud engineering (preference for AWS)
Desired Qualifications
- Prior experience in Commodities, Fixed Income, Equities, Asset Management is a plus
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