Software Development Manager - Observability Platform

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. We treat the platform as a product, with our internal engineering teams as our customers.

Our mission is to provide the best, most consistent logging, metrics, and tracing experience. We do this by brokering tools and patterns into golden paths that accelerate best practices, and by connecting teams to business impact through SLOs, user flows, and customer experience signals. We instrument on open standards so that switching costs are a configuration change rather than a rewrite, we optimize for the questions engineers did not anticipate rather than for pre-built dashboards, and we design for a world where both humans and AI agents investigate production through fast, high-cardinality data.

As the founding Software Development Manager for this team, you'll hire and lead the engineers who build that foundation, and you'll set the technical vision that shapes how Wealthsimple understands its systems for years to come.

In this role you'll have the opportunity to:

• Lead an impactful team with a lot of visibility. You'll own career development, performance management, coaching, and a culture of technical excellence, collaboration, and continuous improvement.
• Define what observability means at Wealthsimple, articulate a multi-year roadmap, and align engineering and leadership behind it. You turn a vision into a sequenced plan and then into shipped platform capabilities.
• Build the wide-event data model and the golden paths on top of it. Lead the design of an events-first foundation on open standards such as OpenTelemetry , including the shared SDKs, libraries, and instrumentation defaults that make rich, consistent telemetry the path of least resistance for every team.
• Drive the company's detection and reliability goals. Lead the work that reduces mean time to detect on key user flows, using SLOs and customer-experience signals that catch issues before customers feel them, rather than alerts that only report machine state.
• Make production legible to AI agents. Build the fast, high-cardinality query foundation and the 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.
• Run experiments and prove value on pilots. Establish a test-and-learn approach, starting with one or two pilot teams to validate the approach before scaling it across the organization.
• Own the tool and vendor strategy. Shape the build, buy, and broker decisions across the observability stack, including how we get the most from Datadog while reducing lock-in and managing cost.
• Stay hands-on. Contribute to critical architectural decisions, review complex designs, and get into the code when it will unblock the team or prototype a new approach.
• 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.

What you'll bring:

• 7+ years in software engineering, with a software development background rather than a primarily operations or systems-administration one. You build platforms and tools as software, with the testing, design, and engineering rigor that implies.
• 3+ years of engineering management experience, developing engineers and delivering complex technical initiatives through both growth and change.
• Direct, hands-on experience building an observability or telemetry platform before. You have implemented this kind of roadmap at least once, so you are not learning the problem space on the job. You do not need to have built a commercial product such as Datadog or Honeycomb , but you have built or implemented the equivalent capability inside an engineering organization.
• Experience with event-based systems. You understand wide structured events, high-cardinality data, columnar or streaming backends, sampling, tagging, and context propagation, and why these matter for asking questions you did not anticipate.
• A track record of building SDKs and shared platforms in a platform or foundations engineering team. You have shipped the libraries, paved roads, and defaults that other engineers build on, and you treat those internal engineers as customers.
• Fluency with open standards and instrumentation. Hands-on experience with OpenTelemetry or an equivalent, and with SLI and SLO design, is core to how you think.
• The ability to set a vision and a mission and move an organization toward it. You can define direction, sequence the work, and bring engineering and leadership along.
• Comfort running experiments. You are data-informed, you frame work as hypotheses to validate, and you are willing to pilot, measure, and adjust rather than commit everything up front.
• Strong people leadership. You grow careers, give clear feedback, build inclusive teams, and attract and retain strong engineers.
• Collaboration and influence across boundaries. You build trust with peer managers, senior leadership, and partner teams, and you communicate clearly to technical and non-technical audiences.

Nice to have:

• Experience in a regulated or fintech environment, familiarity with Kubernetes and progressive delivery such as Argo Rollouts , experience with columnar stores such as ClickHouse , and experience building observability for LLM and agent-based workloads.