S
Silvertide

Graduate Software Engineer

Expired
Applications closed: 16/09/2026

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Sectors

Technology
Software engineering

Locations

London | Graduate | Full-time

About us

SilverTide is a financial markets analytics company with offices in London and Dubai. We provide institutional hedge funds and asset managers with derivatives market research through a proprietary data and analytics platform, alongside trade execution with banks and market makers. Our clients are discretionary portfolio managers who depend on the quality of our research output.

Our engineering team is small — under 10 people — building the full stack ourselves: Python, Polars, FastAPI, TimescaleDB, Prefect, FastMCP, Redis and Azure, with Dash on the front end and QuantLib in the quant layer. Joining a team this size means direct ownership of what you build and close contact with the people using it, not a narrow slice of a much larger codebase.

About the role

We're hiring a permanent software engineer to work primarily on integrating AI/LLM capabilities into our analytics platform — think automated research workflows, natural-language interfaces onto our derivatives data, and AI-assisted tooling for our quant, research, and execution teams. You'll also get exposure to the wider stack (data infrastructure, quant library development) as the team's needs evolve, but AI engineering integration is where you'll spend most of your time.

This is a strong fit for a graduate who wants to move into finance and apply software engineering skills to real market-facing problems, without needing prior finance experience.

Responsibilities

  • Design and build AI/LLM-powered features on our analytics platform — from prototyping to production
  • Integrate AI tooling with our existing data pipelines and quant library
  • Contribute to the broader platform (data engineering, analytics tooling) as needed
  • Work directly with the quant and research teams to turn their workflows into shippable tools

Requirements

  • Strong Python development experience
  • A degree (or equivalent) in computer science, mathematics, physics, engineering, or another quantitative discipline
  • Evidence of hands-on AI/LLM engineering — a project you've built, not just familiarity with the space
  • Comfortable working in a small team with direct ownership of your work

Nice-to-haves

  • Interest in financial markets, rates/derivatives in particular
  • Experience with cloud infrastructure (Azure or similar)
  • Experience with high-performance computation
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