Principal Architect, AI & High Performance Systems

Job requirements

• Assess the environment: run architecture, AI-readiness and workload-performance diagnostics inside the customer's environment, and turn the findings into a defensible design.

• Identify accelerated-compute opportunities: assess workloads for GPU and accelerated-compute opportunities, and prove the case with numbers.

• Evaluate AI and agent use cases: feasibility, architecture, cost and what it takes to operate them. Saying “not yet, and here's why” is part of the job.

• Design across the estate: one coherent system spanning KX technology, AI platforms and the customer's own data, not four loosely-joined ones.

• Map the data estate: work alongside the customer's quants, data owners and domain specialists to understand the estate and its ontology, and the opportunities to leverage that data.

• Quantify the gains: size the gains in latency, throughput, scalability and cost credibly enough to survive the customer's own engineers.

• Define the engagement hypothesis: define the architecture and what each engagement is trying to prove, and how we will know.

• Benchmark and prototype: benchmarks and rapid prototypes on real customer data, with results you would publish.

• Define the evaluation framework: agree how each AI or agent system will be measured before it is built: golden sets, accuracy and recall, regression tests, and latency and cost benchmarks. Architecture that cannot be evaluated cannot be defended.

• Lead through to production: senior technical leadership through the first production outcome, not a slide deck and a handover.

• Build reusable assets: reusable diagnostics, reference architectures and accelerators so each engagement starts further forward than the last.

• Inform the product roadmap: turn repeated customer requirements into clear inputs for Product and Engineering.

• Deep understanding of distributed systems, real-time processing, streaming architectures and system performance: you know why something is slow, not just that it is.

• Strong cloud architecture skills and strong Python.

• A working understanding of AI and agent-system architecture: model integration, tools, context, and how enterprise data actually gets to a model safely.

• Credibility with CTOs, Chief Data and AI Officers, platform leaders and senior engineers. You can hold all four conversations in the same week.

• Strong capital-markets experience building front-office systems (trading, pricing, market data, risk or research platforms) in production and under real market conditions.

• A track record designing and delivering production AI, data-platform or high-performance computing systems at scale.

• Practical experience with GPU or other accelerated-compute technologies.

• Experience designing evaluation frameworks for AI systems: agreeing what correct means with domain experts, building golden sets, and measuring accuracy, recall, latency and cost honestly enough to support a deployment decision.

• Experience bench-marking workloads and diagnosing performance, scalability and cost.

• Experience operating in complex, secure or regulated enterprise environments, and the patience that requires.

• Experience with q, kdb+ is highly desirable but not essential. Welcome if you have it; the appetite to become genuinely good at it matters more.

• Equivalent evidence counts. Low-level systems programming in C++, Rust or C, and the performance instincts that come with it: memory layout, cache behaviour, lock-free concurrency, kernel-bypass or FPGA work.

• Depth in another time-series or tick store (OneTick, ClickHouse, InfluxDB, Arctic or an in-house engine), or in array and functional languages (APL, J, OCaml, Haskell, Scala) where the thinking transfers directly to q.

• Cloud Certifications desirable but not essential.

Job responsibilities

• Hybrid working model based out of our New York Toronto Office. Occasional visits to client site expected.

Job benefits

• Competitive Salary

• Individually tailored training and skills ndevelopment

• Private healthcare package and Employee Assistance Programme

• Enhanced maternity and paternity package

• Wellness Days and Volunteer Days

• Salary Range: 150,000 - 350,000 USD dependent on experience and location