Software Developer; Research

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it.
DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

We build the systems that turn real-world events into actionable signal, at low latencyand high reliability in a trading environment where being right second is the same asbeing wrong. This role sits at the intersection of research and infrastructure: you'llform hypotheses, prove them with rapid analysis, and then build the production systems that act on them.

We also build with LLMs as a first-class part of the toolchain, not a side experiment.

The people who do well here are the ones who can wield an agentic harness as fluently as
they wield a profiler and who know exactly where each one stops being trustworthy.

• Expand our event-driven strategy across exchange feeds, market news, social media, and infrastructure telemetry.
• Spin up rapid analyses in Python/Jupyter to assess signal quality, and turn what you find into system improvements.

• Build and operate agentic harnesses — tools, context management, evals, guardrails — that do real work against our data and infrastructure, and own their quality in production.
• Apply LLMs where they genuinely win (extraction, classification, triage, research acceleration) and make the call to not use one where they don't.

• Own full-stack performance from the network edge to in-memory stores — instrumenting, monitoring, and debugging production systems alongside operations, keeping SLOs razor-sharp.
• Lead green-field initiatives, design reviews, and post-mortems.

• 3-5 years
  building real-time or data-intensive systems (we weigh trajectory and depth over the exact number).
• Depth with LLMs, not just usage
  — how these models actually behave (context and its failure modes, tool use, structured output, cost/latency trade-offs, bounding hallucination) and how to build the harness around one: tools, memory, retries, evals, human-in-the-loop boundaries. Bring something real you shipped and can walk us through end to end, including what broke.
• Strong engineering fundamentals in Python, Go, or Rust.A preference, not a gate — deep systems experience in another serious language transfers.
• Deep knowledge of network programming and protocols
  — TCP/UDP/IP, DNS, BGP, HTTP(S), Web Socket, QUIC.
• Rapid POCs to production
  — validate statistical significance, iterate quickly, ship, and explain the result to technical and non-technical audiences alike.
• Bachelor's or Master's in Computer Science, Data Science, Mathematics, or a related discipline.

This is a competitive, high-stakes environment, and we're looking for people who want that
rather than tolerate it. You'll likely recognize yourself here if:

• You want problems that are genuinely hard and measurable — where the scoreboard is real and public inside the team.
• You move fast…