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About the Role:As a Site Reliability Engineer, you'll lead reliability and infrastructure projects that span multiple teams and business domains. Decisions you make on system design, tooling, and process will directly shape how the teams you work with build and operate at scale.
To drive success in this role, you will have a strong background in cloud infrastructure and platform engineering, with experience across infrastructure-as-code, CI/CD and release automation, observability, security, and disaster recovery. You should possess strong technical judgement, the ability to independently lead complex projects from design through delivery, and a proactive approach to eliminating operational risk before it becomes a problem.
Regular collaboration with software engineering teams, security teams, and other relevant stakeholders will be key in ensuring the reliability and efficiency of our production systems are achieved.
Key Responsibilities:- Analyze, test, and evolve systems to improve reliability and performance at an architectural/infrastructure level, leading medium-to-large projects from design through delivery
- Apply AWS and GCP expertise to architect and build reliable, highly-available cloud infrastructure across multiple products and projects
- Implement observability strategy and standards, developing the tooling and dashboards other teams build on
- Champion SLOs and error budgets for services in your area, using them to prioritise reliability work against feature velocity
- Act as incident commander for significant production incidents, lead troubleshooting on complex issues, using blameless post-mortems to drive continuous improvement
- Reduce operational toil by building automation and self-service tooling, that other engineers can adopt, rather than absorbing repetitive work yourself
- Develop and maintain design, troubleshooting, and runbook standards that other engineers can follow
- Apply AI-assisted development to infrastructure problems, and guide other engineers on using AI tools effectively within your team's workflows
- Contribute to capacity planning and cost optimisation
- Mentor other engineers on systems thinking, incident management, and production ownership, raising the bar within your team
- Implement security best practices in infrastructure development and maintenance - such as least-privilege access, secrets management, policy-as-code gates in your pipelines
What you will bring:- 3+ years of experience in SRE, Platform Engineering, DevOps or other related roles
- Strong understanding of SRE and platform engineering principles, with experience applying them to lead cross-team projects
- Experience using and configuring modern observability tools such as Datadog, Elasticsearch, Prometheus, Grafana
- Experience with cloud native and container technology such as Docker, and hands-on experience using and managing Kubernetes clusters
- Experience authoring reusable, parameterised infrastructure-as-code modules (e.g. Terraform)
- Comfortable scripting and developing internal tooling with Bash and at least one programming language (e.g. Python, Go)
- Fluent with AI-driven development environments like Cursor, Claude Code, or Codex, with a proven ability to leverage these tools within production engineering workflows
- Experience working with Linux
- Strong understanding of networking, distributed systems, and system architecture at scale
- Proven experience deploying, scaling, and monitoring web applications and databases in high-availability environments
- Deep expertise in AWS and/or GCP platforms
- Bachelor's degree in Computer Science/Engineering, a postgraduate degree and/or record of academic achievement is also desirable
What you will have:Ownership & Delivery- Takes ambiguous problems and drives them to shipped outcomes - not just code, but results, and takes accountability even without a clear owner
- Balances speed with quality - knows when to iterate fast and when to invest in durability
- Manages risk proactively - identifies failure modes and mitigates before they bite
Communication & Influence- Creates clarity from ambiguity; documents decisions so others can build on your work
- Influences through evidence and collaboration, not authority - mentors and unblocks teammates
- Communicates technical concepts clearly to engineers, product, and business stakeholders
AI-First Mindset- Treats AI tools as essential infrastructure, not optional add-ons - continuously experiments with new capabilities
- Understands LLM strengths and limitations - knows when to prompt and when to build differently
- Thinks in leverage: automates the repetitive, focuses human attention on judgement calls
- Helps others adopt AI workflows, shares what works, and raises the floor for the whole team
Flexible Work Environment - Our teams are hybrid. We work from home on a Wednesday and Thursday and attend the office on Monday, Tuesday and Friday with flexibility around start/finish times.
*This position offers a base salary range of C$115,000 to C$145,000 annually.
