Building a Senior AI Engineering Team (LLM + Distributed Systems)
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Global Investment Bank | Capital Markets Platform
London (1–2 days onsite)
£700–£1,200/day (Outside IR35) Contract to permanent available
The Mandate
We are building a production-grade AI platform inside a global investment bank.
This is not a research team or a chatbot project.
This is engineering-heavy, focused on integrating LLM systems into large-scale, distributed environments used by trading and quant teams.
We are hiring across multiple levels:
- Lead Engineer (Agentic / RAG focus)
- Architect (end-to-end platform design- Agentic / RAG focus)
- Senior Engineers (x3) Agentic / RAG focus
- Potential Director-level hire to oversee the function
What This Role Requires (Read Before Applying)
You must have:
- Strong background in backend or data engineering
- Proven experience working on production systems with real users
- Hands‑on experience with LLMs in production (RAG, embeddings, etc.)
If your experience is limited to courses, side projects, or chatbot builds, this role is not a fit.
What You’ll Be Working On
- LLM-powered systems integrated into enterprise‑grade platforms
- RAG pipelines over large internal datasets (structured + unstructured)
- High‑throughput, low‑latency services
- Multi‑step workflows combining LLMs, data pipelines, and external tools
- Systems requiring reliability, observability, and auditability
Core Technical Requirements
- Strong Python (Java/Scala also relevant)
- Experience with distributed systems, APIs, microservices
- Familiarity with event‑driven systems (Kafka or similar)
- LLM experience:
- RAG
- embeddings
- vector search / semantic retrieval
Strong Preference
- Experience working in high‑scale environments (tech, fintech, data platforms) xwzovoh
- Exposure to regulated or high‑control systems
- Experience designing or owning end‑to‑end systems
What This Role Is NOT
- Not a prompt engineering role
- Not a research position
- Not suitable for candidates without large‑scale system experience
Why This Role
- Build real AI systems in production, not demos
- Join early in a high‑impact, well‑funded build
- Work alongside senior engineers and platform teams
Apply
If you’ve built systems that operate at scale and have deployed LLM solutions into production, we want to hear from you.
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