Staff Software Engineer, Observability Platform
Wealthsimple Remote (Canada)Est. Est. CAD 130,000–170,000 / yearLead
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Llm
Build something people love
Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.
We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work .
About the Observability Platform Team
The Observability Platform team exists to make production legible to every engineer and AI agent at Wealthsimple, on their first day and every day after. Every request, job, and user action produces a signal, and our job is to turn that signal into a fast, high-cardinality data asset that anyone can question. A business stakeholder investigating a drop in conversions, a service owner tracing a slow endpoint, an engineer validating a release, and an AI agent confirming its own change should all reach for the same data and get an answer in seconds.
We treat the platform as a product, and the engineers, service owners, and business stakeholders who depend on it as our partners. Our mission is to build the wide-event data model, the query foundation, and the golden paths that connect people to production data. We instrument on open standards such as OpenTelemetry so switching costs are a configuration change rather than a rewrite, and we optimize for the questions people did not anticipate rather than for pre-built dashboards.
As the Staff Software Engineer on this team, you are the deepest technical builder and the person who sets the technical bar. You design the foundations, write the code that matters most, and raise the engineering quality of everyone around you.
In this role you'll have the opportunity to:
Design and build the events-first foundation. Own the architecture of the wide-event data model and the high-throughput ingest, storage, and query pipelines behind it, including the high-cardinality and columnar or streaming systems that make arbitrary questions answerable in production, whether they come from a business stakeholder, a service owner, an engineer, or an AI agent.
Build the SDKs and golden paths. Design and ship the instrumentation libraries, shared SDKs, and defaults that make rich, consistent telemetry the path of least resistance for every engineering team, and drive their adoption.
Set the technical standards. Define the instrumentation conventions, naming, tagging, sampling, and context-propagation practices on open standards such as OpenTelemetry, and codify them so humans and AI agents share one language.
Make production legible to AI agents. Build the fast query foundation and access patterns, including protocols such as MCP, that let AI agents investigate incidents, verify their own changes, and operate in tight feedback loops alongside engineers.
Move fast with AI tooling. Use AI coding tools such as Claude Code and modern LLMs fluently to prototype, build, and navigate large systems, and help the team raise its own bar for building with AI.
Work confidently in ambiguity. Jump into unfamiliar codebases and make significant, well-reasoned changes with high impact.
Prove value through experiments. Pilot new approaches with one or two teams, measure the results, and scale what works rather than committing everything up front.
Raise the bar for others. Mentor senior engineers, review complex designs, and lead cross-team technical initiatives through influence rather than authority.
What you'll bring:
Significant software engineering experience, typically 8+ years, with a software development background. You build platforms and tools as software, with the design, testing, and engineering rigor that implies.
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