Founding Software Engineer

Hartleyco — United Kingdom · Posted ~1 day ago

Senior Full-time £80000-£110000 + meaningful equity

Skills

Python Production-grade data engineering Large-scale financial datasets Data pipelines Risk modeling Backtesting Scenario analysis Stress testing Systematic strategy concepts Software architecture Ownership in early-stage environments C++ Rust Data engineering APIs

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Summary

An early-stage founding engineering role for a strong Python engineer who wants end-to-end ownership. You will build quantitative risk models, backtesting and stress-testing infrastructure, high-volume financial data pipelines, APIs, and an AI-powered research layer for professional users. The role suits someone comfortable making architectural decisions, working with ambiguity, and taking responsibility for entire systems. Exceptional recent graduates with highly relevant internships may also be considered.

Highlights

Exceptional founding-stage opportunity with significant technical ownership, meaningful equity, and the chance to shape core systems from the ground up. Work spans quantitative modeling, large-scale data engineering, APIs, and research infrastructure in a fast-moving environment.

Description

Founding Engineer - Quant AI Platform London preferred, open to strong candidates across the UK £80k–£110k + meaningful equity We're working with an early-stage fintech startup building a next-generation platform for professional investors, covering portfolio risk analytics, scenario modelling, and an AI-driven research layer that sits on top of a genuinely massive financial dataset. The company is already live with paying fund clients and closing in on a seed round. They're hiring two Founding Engineers to join at the ground floor. This isn't a "join a team" role, it's ownership of entire systems: from the underlying math and data pipelines through to the APIs and the interfaces that traders and analysts actually use. What you'll be doing Building and owning risk models, backtesting infrastructure, and scenario/stress-testing toolsWorking with large-scale, point-in-time financial datasets at serious volumeShaping the data and strategy layer that powers an AI research assistant for professional investorsMaking real architectural calls in a small, fast-moving team What we're looking for Strong Python and production-grade data engineering experienceC++ or Rust is a bonus, not a requirementBackground in a fund, bank or risk environment (or comparable exposure to serious financial datasets)A working understanding of portfolio risk, backtesting, or systematic strategy concepts, gained through real projects rather than just interestC++ or Rust is a bonus, not a requirementExceptional recent graduates with strong relevant internships (e.g. at top quant funds) will also be consideredComfortable with ambiguity and genuine ownership in an early-stage environment Process: a Python-based technical exercise focused on working with large datasets, followed by a conversation with the founders. Get in touch if this sounds like you, or if you know someone who fits.