Quantitative Developer

Senior Quantitative Developer

Location: London, UK (Full-time, In-office)

Experience: 5–8 Years

Compensation: Circa £160,000 Base + Performance-Linked Bonus

Are you ready to architect the next generation of autonomous trading? We are representing a top-tier London Hedge Fund looking for a Senior Quantitative Developer to build a fully automated, AI-driven systematic trading system.

This role is for a specialist who doesn't just use tools but masters the underlying architecture. You will be responsible for integrating Claude (Anthropic) and advanced AI frameworks into a live production environment to generate alpha in the Equity Options markets.

You will be the custodian of a massive, high-fidelity data library. We aren't looking for "standard" Python users; we need an engineer who can optimize at the edge of performance:

• Massive Throughput: Design scalable infrastructure to handle massive data loads
  , ensuring sub-millisecond processing times for large-scale financial datasets.
• Historical Depth: Processing per-minute data points spanning 24 years of market history.
• Vectorized Performance: Moving beyond Pandas—leveraging Polars for multi-threaded, Rust-backed data manipulation and Dask for distributed compute across clusters.
• Execution Engine: Native integration with Spider Rock for complex Equity Options execution and automated risk-routing.

• System Architecture: Build an end-to-end automated trading system from scratch using a modern, AI-first stack.
• AI Integration: Leverage Claude and LLMs for signal extraction, code optimization, and autonomous strategy refinement.
• High-Performance Computing: Implement predicate pushdown and efficient Parquet/Arrow storage to ensure backtests on decades of data run in minutes, not days.
• Options Logic: Programmatically handle Greeks, volatility surfaces, and risk management through the Spider Rock API
  .

• Experience: 5–8 years in a Quant Dev or Systematic Trading environment at a top fund or bank.
• Coding Mastery: Expert proficiency in Python (Polars/Dask/FastAPI) and/or C++.
• AI Native: Proven ability to use LLMs and Machine Learning to solve complex financial time-series problems.
• Industry Standard
  
  Experience:
  
  You have worked with industry-standard large data before and understand the nuances of point-in-time integrity.
• Equity Options Knowledge: Specific experience with options Greeks and execution platforms (Spider Rock is highly preferred).

• Total Rewards: A highly competitive base salary of £160k with a significant bonus structure that rewards PnL contribution.
• Elite Environment: Work alongside the best minds in London in a high-conviction, low-bureaucracy trading floor.
• Tech Freedom: You will have the mandate to use the best emerging tech (Claude, Rust-based tools) to win.