# Software Development Manager, Observability Platform
**Company:** [Wealthsimple Technologies](https://scaleengineer.com/companies/wealthsimple)
Lead the founding Software Development Manager role for Wealthsimple's Observability Platform team, responsible for building production telemetry infrastructure that empowers all engineers and AI agents with logging, metrics, and tracing capabilities. This position combines strategic platform vision-setting with hands-on technical leadership, requiring deep expertise in observability architecture, event-based systems, and OpenTelemetry standards. You'll manage and grow an engineering team while defining multi-year roadmaps, establishing golden paths for observability best practices, and architecting systems that support both human and AI-driven incident investigation.
**Role:** Engineering Manager
**Seniority:** Manager
**Locations:** Remote (Canada)
**Remote:** yes
**Salary:** 160000–220000 CAD
[Apply](https://jobs.ashbyhq.com/wealthsimple/b0271319-e7bc-4a4e-94ea-a6cffb23d6f2)
Canonical: https://scaleengineer.com/jobs/wealthsimple/software-development-manager-observability-platform
---
## Responsibilities

- Team Leadership and Development: Hire, mentor, and manage software engineers on the Observability Platform team. Own career development, performance management, coaching, and foster a culture of technical excellence, collaboration, and continuous improvement while building an inclusive, high-performing engineering organization.
- Observability Vision and Strategy: Define observability standards and direction for Wealthsimple, articulate a multi-year technical roadmap, and align engineering teams and leadership behind a cohesive vision. Translate strategic objectives into sequenced platform capabilities and measurable outcomes.
- Events-First Architecture Design: Lead the design and implementation of a wide-event data model built on open standards such as OpenTelemetry. Architect shared SDKs, libraries, and instrumentation defaults that make consistent, rich telemetry the path of least resistance for all engineering teams across the organization.
- Reliability and Detection Excellence: Drive the company's detection and reliability initiatives by reducing mean time to detect on critical user flows. Implement SLI and SLO frameworks that catch production issues before customers are impacted, moving from machine-state monitoring to customer-experience-signal-driven alerts.
- AI-Agent Integration and High-Cardinality Querying: Build fast, high-cardinality query foundations and access patterns including Model Context Protocol that enable AI agents to investigate incidents, verify deployment changes, and operate in tight feedback loops alongside human engineers for accelerated incident resolution.
- Pilot Validation and Experimentation: Establish a test-and-learn methodology by running pilots with select teams to validate observability approaches before organization-wide scaling. Use data-informed decision-making to prove value, iterate on implementations, and measure impact before full deployment.
- Tool and Vendor Strategy: Own build-vs-buy-vs-broker decisions across the observability stack. Maximize value from existing tools like Datadog while reducing vendor lock-in, managing costs, and ensuring the technology portfolio supports long-term strategic flexibility and scalability.
- Hands-On Technical Contribution: Remain actively involved in critical architectural decisions and complex technical design reviews. Contribute directly to the codebase when necessary to unblock teams, prototype innovative approaches, and maintain technical credibility while demonstrating platform engineering best practices.
- AI-Assisted Development Leadership: Fluently leverage modern AI coding tools such as Claude Code and large language models to prototype solutions, navigate complex systems, and accelerate development velocity. Lead by example in raising the team's capability and comfort with AI-assisted software development practices.
- Cross-Functional Collaboration: Build trust and influence across engineering teams, peer managers, and senior leadership. Communicate observability vision and technical decisions clearly to both technical and non-technical stakeholders, ensuring alignment and buy-in across organizational boundaries.

## Requirements

### education

- {"name":"Bachelor's Degree in Computer Science or Related Field","description":"Formal education in computer science, software engineering, electrical engineering, mathematics, or equivalent practical experience demonstrating equivalent knowledge in software engineering fundamentals and system design."}

### technical

- {"name":"Platform Engineering and Observability Architecture","description":"Demonstrated expertise in designing and implementing observability or telemetry platforms within engineering organizations. You have built or implemented the equivalent of commercial products like Datadog or Honeycomb internally, understanding logging, metrics, and distributed tracing infrastructure at architectural scale."}
- {"name":"Event-Based Systems and High-Cardinality Data","description":"Deep hands-on experience with wide structured events, high-cardinality data modeling, columnar or streaming backends, sampling strategies, context propagation, and tag-based cardinality management. You understand the architectural trade-offs that enable asking unanticipated questions of production data."}
- {"name":"OpenTelemetry and Open Standards","description":"Practical, hands-on fluency with OpenTelemetry standards, instrumentation patterns, and SDK development. Experience designing SLI and SLO frameworks that drive reliability engineering practices and inform product decisions."}
- {"name":"SDK and Platform Library Development","description":"Track record of shipping SDKs, shared libraries, paved-road frameworks, and instrumentation defaults that other engineers build upon. Experience treating internal engineers as customers and designing APIs that prioritize developer experience and adoption."}
- {"name":"Datadog and Observability Tools","description":"Hands-on experience with Datadog or similar enterprise observability platforms, including configuration, optimization, cost management, and strategic decisions around tool selection and vendor relationships in observability stacks."}
- {"name":"AI and Modern Development Tooling","description":"Fluency with AI coding assistants (Claude Code, GitHub Copilot, etc.) and large language models for software development. Ability to leverage AI tooling for rapid prototyping, code navigation, and problem-solving in complex systems."}

### experience

- {"name":"Software Engineering Leadership (3+ years)","description":"Minimum three years of hands-on engineering management experience with a track record of developing software engineers, delivering complex technical initiatives, and leading teams through organizational growth and technical change."}
- {"name":"Core Software Engineering (7+ years)","description":"Seven or more years of software engineering experience with a strong background building software platforms and tools, not operations or systems administration. You apply software engineering rigor including testing, design patterns, and architectural principles to platform development."}
- {"name":"Observability Platform Implementation","description":"Direct hands-on experience building or implementing observability and telemetry platform capabilities. You have executed this type of roadmap at least once and understand the problem space deeply rather than learning it on the job."}
- {"name":"Platform Foundations Engineering","description":"Experience in platform or foundations teams shipping shared infrastructure, SDKs, and internal developer tooling. You have built the libraries and frameworks that other engineers depend on and understand the customer-centric mindset required for internal platforms."}

## Skills

### required

- {"name":"Software Architecture and Systems Design","description":"Expert-level ability to architect scalable, distributed systems. Strong grasp of design patterns, trade-offs between consistency and availability, and the capacity to make sound architectural decisions that balance performance, maintainability, and cost."}
- {"name":"Observability and Telemetry Expertise","description":"Deep understanding of logging, metrics, and tracing paradigms. Proficiency in designing high-cardinality telemetry collection, understanding cardinality explosion problems, sampling strategies, and query optimization for production observability systems."}
- {"name":"Engineering Management and Leadership","description":"Proven ability to hire, mentor, and develop software engineers. Experience with performance management, clear feedback delivery, career coaching, and creating inclusive, psychologically safe team environments that attract and retain talent."}
- {"name":"Strategic Vision and Execution","description":"Capability to define technical direction, create multi-year roadmaps, sequence work intelligently, and bring diverse stakeholders along through clear communication and demonstrated impact. Ability to translate vision into actionable work and measurable outcomes."}
- {"name":"OpenTelemetry and Instrumentation Standards","description":"Working knowledge of OpenTelemetry standards, semantic conventions, and instrumentation best practices. Experience designing SDKs and instrumentation libraries that encourage adoption and consistent telemetry collection across teams."}
- {"name":"Hands-On Coding and Technical Depth","description":"Ability to write production code in modern programming languages, review complex code for correctness and design, and jump into codebases to prototype solutions or unblock teams. Maintains technical credibility and current skills despite management responsibilities."}
- {"name":"Data-Driven Decision Making","description":"Comfort framing work as testable hypotheses, designing experiments and pilots to validate approaches, and making decisions based on evidence. Willingness to iterate, measure, and adjust rather than commit everything upfront."}
- {"name":"Cross-Functional Communication","description":"Ability to communicate complex technical concepts clearly to non-technical audiences including executives, product managers, and business stakeholders. Strong interpersonal skills for building trust and influencing across organizational boundaries."}

### preferred

- {"name":"Regulated Industry and Fintech Experience","description":"Prior experience working in regulated environments such as fintech, financial services, healthcare, or compliance-heavy industries. Understanding of regulatory considerations, security requirements, and risk management in production systems."}
- {"name":"Kubernetes and Progressive Delivery","description":"Hands-on experience with Kubernetes orchestration and progressive delivery frameworks such as Argo Rollouts. Knowledge of deployment patterns, canary releases, and automated rollback strategies for production reliability."}
- {"name":"Columnar Data Stores and Analytics","description":"Practical experience with columnar databases such as ClickHouse, Apache Druid, or similar high-cardinality analytics platforms. Understanding of query optimization, data compression, and time-series analysis at scale."}
- {"name":"LLM and AI Agent Observability","description":"Experience designing observability solutions for large language models and AI agent workloads. Understanding of unique observability challenges in generative AI systems, token tracking, and cost monitoring for LLM applications."}
- {"name":"Model Context Protocol (MCP)","description":"Familiarity with Model Context Protocol standards and patterns for enabling AI agents to interact with external systems and data. Experience building or integrating MCP-compatible tools for agent-based workflows."}
- {"name":"Argo and GitOps Patterns","description":"Experience with Argo CD and GitOps deployment patterns, including declarative infrastructure management, automated synchronization, and continuous deployment practices."}

## Tech stack

### tools

### others

### databases

### languages

### frameworks

## Benefits

### benefits

## Compensation

- **max:** 0
- **min:** 0
- **currency:** 
- **stockOptions:** false

## Interview process

### steps

## Full description
## **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 $125 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](https://www.wealthsimple.com/en-ca/culture) and learn more about [how we work](https://www.wealthsimple.com/en-ca/careers).

## **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.

## **Why Wealthsimple?**

🌸 Top-tier health benefits and life insurance

📈 Long-term group savings with employer match, through Wealthsimple for Business

🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year

✈️ 90 days away: work outside Canada for up to 90 days per year

👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS

🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.

## **ICYMI**

**Technology & Innovation at Wealthsimple:** We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.

**Inclusion Statement:** We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.

**Accessibility Statement:** We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.

**AI in Hiring:** We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.