Quant Developer | Low-Latency Systems Engineer (Rust, C++20, Python)

Most financial software is built by engineers who understand code but not markets — or traders who understand markets but not systems. I sit at the intersection of both, and that distinction matters when you need something that doesn't just run, but runs correctly under real market conditions.

I specialize in high-performance quantitative systems: execution engines, pricing models, real-time data pipelines, and arbitrage infrastructure. My work is written in Rust, C++20, and Python, with an emphasis on correctness first, then performance — because a fast system with wrong numbers is worse than a slow one.

Systems I have designed and shipped:

A lock-free, nanosecond-latency spatial arbitrage engine in Rust/C++20 targeting BTC/USD and ETH/USD across Binance and Coinbase — built with SPSC ring buffers, RDTSC timestamping, zero heap allocation on the hot path, and fixed-point arithmetic at 1e8 precision. Engineered with a mandatory kill switch gating every order on six real-time risk conditions: daily loss limit, position size, order rate, manual halt, consecutive rejects, and leg timeout.

A production Options Pricing SaaS in Rust implementing the full Black-Scholes model with complete Greeks surface (Delta, Gamma, Theta, Vega, Rho) — served via FastAPI, integrated with Supabase, subscription-gated via Paystack, and deployed live on Render.

A real-time Crypto Arbitrage Signal Dashboard monitoring live BTC/USD and ETH/USD spreads across Binance and Coinbase, with fee-adjusted net profit calculations, signal detection logic, and a live deployment at production uptime.

What I deliver for clients:

Execution and strategy engines for algorithmic and high-frequency trading

Options pricing, risk metrics, and derivatives modelling

Real-time WebSocket data feeds and low-latency infrastructure

Financial APIs and quantitative backends (Rust, C++20, FastAPI, Python)

Backtesting frameworks and walk-forward validation systems

ETL pipelines, analytics dashboards, and data engineering for finance

I do not deliver until the implementation is correct, the edge cases are handled, and the system behaves the way it should under conditions it wasn't designed for. If you are building something where accuracy, latency, or financial integrity is non-negotiable — that is exactly the kind of problem I take on.

Let's talk about what you need built.