Founding Quant Engineer

Location: Central London (Hybrid) | Type: Full-time

Numi is partnering with a stealth, next-generation systematic trading and AI research lab to find their founding engineering hire. They combine machine learning, neuroscience-inspired architectures, and high-performance engineering to build decision engines that operate in live markets, where reliability and precision translate directly into performance. The firm is backed by Tier-1 Silicon Valley and European venture funds. They are already live, running multiple strategies in production across venues on self-built infrastructure that handles real-time data ingestion, low-latency messaging, research compute, and monitoring.

The Team: A small, dense, high-pedigree team consisting of senior ex-professionals from Citadel, XTX, Brevan Howard, and Citi, alongside graduates and postgraduates from Oxford, Cambridge, Princeton, and Cornell. This is a research-lab culture: high trust, high autonomy, low bureaucracy, and a very high bar.

The Role: You will work directly with the founders, researchers, and traders to design and run the internal platform that powers live trading and research. Your mandate is simple: build an infrastructure advantage.

What You’ll Own:

• Production Infrastructure: Multi-region cloud and latency-sensitive environments.
• Reliable Systems: Live trading, multi-venue market data ingestion, and research compute.
• Deployment Pipelines: CI/CD that lets the team ship strategy and model changes quickly and safely.
• Observability: End-to-end monitoring across data quality, execution, strategy, and infrastructure.
• Resilience: Failover, disaster recovery, and operational readiness for systems where downtime has an immediate financial cost.
• Research-to-Prod Pipeline: Bridging the route from research prototype to production service with rigorous testing, monitoring, and maintainability.
• Security Architecture: IAM, networking, secrets management, and access control.
• ML-Serving Infrastructure: Low-latency model serving, feature pipelines, and experiment tooling for proprietary research models.

What the First Six Months Might Include:

• Measurably improving the performance of live strategies (lower latency, tighter execution, better fill quality).
• Hunting "infra alpha"—finding competitive edges derived purely from engineering excellence in data freshness, latency, execution, and routing.
• Building a fast research and backtesting environment, plus the tooling to take new strategies from idea to live with far less friction.
• Establishing a CI/CD pipeline that turns a researcher's validated change into a safe production deploy in minutes.
• Hardening the multi-region footprint with supervised services, automated recovery, and zero single points of failure.
• Creating a single-pane-of-glass view of system health across every venue and service.

Likely Background: You might come from Jane Street, D. E. Shaw, Two Sigma, Hudson River Trading, Optiver, XTX, Citadel, an exchange/market-infrastructure business, or a top infrastructure team at a tier-one technology company. What matters more than the logo: you have built and run production systems where downtime has a real cost, and you have supported researchers or traders before.

Signals They Look For:

• Experience building critical production systems with real consequences for failure.
• Strong reliability instincts under pressure.
• High standards for engineering quality and operational discipline.
• Comfort making decisions with incomplete information and moving quickly.
• A desire for true ownership, not just clearing a ticket queue.

Technical Depth:

• Core Fundamentals: Deep Linux and networking knowledge.
• Cloud: Strong cloud experience, ideally AWS (compute, networking, IAM, storage, observability).
• Languages: Strong Python; experience with C++, Rust, or Go for latency-critical paths is a major plus.
• Infrastructure as Code: Terraform or equivalent.
• Release Engineering: Robust CI/CD and release pipelines.
• Data Systems: PostgreSQL / TimescaleDB, Kafka, Redis, ClickHouse, and low-latency messaging.
• Monitoring: Grafana, Prometheus, Loki, or similar.
• Mindset: A security-first approach to infrastructure design.
• Bonus: MLOps experience (model serving, feature stores, low-latency inference).