We build the systems that turn real-world events into actionable signal, at low latency and high reliability in a trading environment where being right second is the same as being wrong. This role sits at the intersection of research and infrastructure: youll form 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.
How You Will Make an ImpactDiscovery & Research- 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.
LLM & Agentic Systems- 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 dont.
Infrastructure & Technical Leadership- 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.
What You BringCore- 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), WebSocket, QUIC.
- Rapid POCs to production - validate statistical significance, iterate quickly, ship, and explain the result to technical and non-technical audiences alike.
- Bachelors or Masters in Computer Science, Data Science, Mathematics, or a related discipline.
Who Thrives HereThis is a competitive, high-stakes environment, and were looking for people who want that
rather than tolerate it. Youll 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 without being sloppy, and youd rather ship, measure, and correct than deliberate indefinitely.
- Youre comfortable being wrong quickly and in public, and you update rather than defend.
Bonus Points- Depth in the current LLM ecosystem - agent frameworks, MCP, RAG architectures, eval tooling, or local/self-hosted inference.
- Demonstrated success squeezing latency from NGINX, Envoy, or custom load-balancing layers.
- Background in high-pressure domains - trading floors, esports, competitive athletics, or hackathons.
- Open-source contributions, technical blogging, or conference speaking.
What we have to offer you:- Mentorship with experienced software developers, database administrators, and technical project managers
- Continuous learning through paid postgraduate degrees, Dev Lightning talks, online learning support and 1 on 1 language tutoring with Berlitz
- 40 hours of paid volunteer work at the organization of your choice
- Bi-weekly social activities, monthly wellness plan, on-site weekly massages, and games room
- Enjoy daily catered meals (breakfast and lunch) with unlimited snacks and beverages
- Competitive salary, matching RRSP
