Quant Engineering Lead (Python / LLM Tooling)

The mandate:

Our client—a global, multi-asset investment manager—has rolled out cutting-edge large-language-model coding assistants across its Risk & Portfolio-Tech organisation. They now need a senior engineer who can turn “moon-shot” ideas into production tools, guiding the business on what LLMs can really do and delivering rapid-fire prototypes that become mission-critical apps.

What you’ll tackle

• Spot the pain-points across Equities, Credit, Rates and central Risk teams; translate data-flow headaches into buildable tech projects.
• Prototype at pace in Python—leveraging LLM co-pilots—to stand-up analytics services, REST APIs and lightweight Dash/React front-ends.
• Own the full stack: data ingestion (SQL, files, feeds), business logic, web/UI, CI pipelines and Linux deployment.
• Codify best practice for safe, auditable LLM-assisted development; lead code reviews and knowledge-share sessions.
• Stay user-facing—white-board with quants, ask clarifying questions, iterate live and keep comms flowing.

You in a nutshell

• 5 + years building production-grade Python systems for data-heavy businesses; comfortable with tests, version control and optimisation.
• Confident SQL, exposure to REST and messaging (Rabbit, Kafka, etc.), and enough Linux to troubleshoot on the command line.
• UI chops in Dash, Flask or React to whip up proof-of-concept dashboards.
• Solid grounding in financial products & risk metrics—equities, bonds and derivatives; VaR, stress, PnL explain.
• Excellent communicator who never “goes dark”, loves prototyping and isn’t afraid to ask the awkward question.
• A self-starter ready to jump into the deep end and push tech (and yourself) beyond comfort zones.

Bonus points for: prior hands-on with Copilot / CodeWhisperer, AWS data tooling, containerisation and a history of mentoring juniors.

Why join?

You’ll become the go-to explorer for one of the buy-side’s most ambitious data-tech stacks—turning previously impossible ideas into daily reality and watching users’ eyes light up when the numbers land in seconds, not hours.

Interested? Reply with your CV or reach out for a confidential chat.