Forward-Deployed Engineer — Embedded on a High-Frequency Trading Desk

A leading global market maker is hiring engineers who want to sit on the desk — not adjacent to it.This is a hands-on, embedded role for engineers who think like traders and ship like infra teams. You'll plug directly into a desk that trades equities, futures, ETFs, and options as both a market maker and a statistical arbitrageur — running high-volume intraday strategies with holding periods measured from microseconds to seconds. The workflow is fast and well-defined: quants prototype models in Python, you help take them to C++ for production. You'll own the low-latency tooling, pipelines, and venue adapters that turn those models into live P&L — with full responsibility for correctness, risk, and recovery.What you'll do- Build low-latency feeders and venue adapters across equities, futures, ETFs, and options- Own desk-facing data pipelines and normalisation for high-volume tick data- Develop pricing, greeks, and market microstructure tooling- Take statistical arbitrage and market-making models from Python prototype to C++ production- Debug quant code in anger — diagnose why a model is misbehaving in production vs. simulation, separate engineering bugs from model bugs, and fix the right one- Validate against real risk and P&L — not just unit tests- Write and own incident playbooks for execution failures- Ship production-grade Python, C++, and Spark- Act as the technical bridge between traders/quants and central platform teams (execution, SRE, data lakehouse)What you'll bring- Strong engineering skills across Python, C++, and Spark with a real track record of production delivery- Genuinely current on modern C++ — C++20/23 in active use, and on top of where the standard is going: SG14 low-latency work, custom allocators and PMR, the concurrency TS, executors, networking TS, std::flat_map and friends. You don't need to have shipped all of it, but you should know what's landed, what's coming, and which parts actually matter for HFT- Genuine finance domain knowledge — market microstructure, exchange protocols, pricing fundamentals, latency- The ability to read, debug, and reason about quant code written by someone else — and to tell a numerical issue apart from an implementation issue under time pressure- Prior experience embedded with traders or delivering desk-facing systems- Sharp risk awareness for P&L-sensitive codeWho we're hiringWe're not hiring one seat — we're hiring across three levels:- Strong juniors (3–5 years) — past the greenhorn stage, comfortable shipping production code unsupervised, ready to own real systems on a desk. If your first couple of years were the learning curve, we want the next phase.- Mid-level engineers (3–8 years) — can lead projects end-to-end, mentor more junior engineers, and act as the senior technical voice in design reviews. You don't need a manager title to lead — you need the judgment.- Principal-level seniors — staff/principal IC types who code every day and have no interest in becoming managers. The doing, not the managing. If you want to keep your hands on the keyboard for the next decade, this is the seat.The team is deliberately small and flat: roughly 2 quants, 1 data engineer, 1 SRE, and 5 developers. No managers in sight. Everyone ships. That's how the desk is built and that's what we're hiring to preserve.Background we're looking forComputer science majors. We want engineers who think natively in algorithms and data structures and who genuinely understand how networks and operating systems work under the hood — page caches, kernel bypass, TCP behaviour, scheduler quirks, cache lines. The kind of person who was a TA for compilers or data structures in undergrad, and ideally picked up a minor in statistics along the way, is exactly the profile that lands well here. Adjacent majors (math, physics, EE) can work if the CS fundamentals are genuinely there — but bootcamp-to-SWE paths and self-taught-only backgrounds aren't the right fit for this seat.The litmus testThree questions to ask yourself before applying:- Can you implement std::vector from scratch in C++ — growth policy, move semantics, exception safety, iterator invalidation, the lot?- Could you architect an order management system that handles race conditions in a sub-microsecond environment — lock-free data structures, memory ordering, contention under load?- Do you genuinely understand conditional probability, Bayes' rule, and the law of large numbers — not as textbook formulas, but as the lens you'd use to reason about a noisy signal over millions of trades?How to read your score:- Three confident yeses → apply at any level. We should talk.- Two yeses and one "not yet" → apply for the junior seat only, and tell us in your note which one is the gap and how you're closing it. Mid and senior require all three.- One or zero yeses → this isn't the right seat right now. Come back when it is.Why this seatThis isn't a platform role with a trader stakeholder once a quarter. You'll sit on a market-making and stat arb desk where decisions are fast, feedback is immediate, and the work moves money the same day. The team is small, the surface area is wide, and the impact is direct.Bonus is tied directly to the trading desk's P&L. What the desk makes, you share in — as a team, not on individual attribution games. Several strategies on the desk have serious scaling plans ahead: meaningfully more capital, more venues, more volume. That means a lot of work, but in the current environment the upside for the people who build it is going to be exceptional. If you want a seat where what you ship is directly tied to what you earn, this is one of the cleaner versions of that trade in the industry.Compensation - Strong juniors (3–5 years): $350k – $500k total comp Mid-level engineers (3–8 years): $500k – $700k total comp Principal-level seniors: $650k – $950k+ total compInterested? Apply below or DM.#Hiring #TradingTech #LowLatency #StatArb #MarketMaking #QuantDev #HFT #PrincipalEngineer #ComputerScience #CppDev