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Counterpart Health

Software Developer - Engineering Productivity

RemoteCanada only
Published
Role
DevOps
Experience
Senior
CAD 115k–CAD 145k/yr
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Open to CA only. Set where you work from to check your eligibility.

No BS summary

Backend/platform developer with 5+ years in software, developer infrastructure, SDLC observability, cloud, IaC, and production telemetry. Needs to be based in Canada and comfortable with regular early-morning or evening calls with Hong Kong colleagues. Load/performance testing and AI-assisted testing architecture matter here.

Core skills

GCP/AWSInfrastructure as CodeSDLC observability

Required skills

Python/GoGitHubLinearSentryGrafanaincident.ioAPIs

Optional skills

GitLabJiraDatadogk6LocustGatlingJMeterGemini

What you'll do

  • Design and champion internal Quality Programms: Drive engineering-wide process changes and ensure pods adopt new reliability standards without friction.
  • Operate with a product-owner mindset to define and evangelize the internal reliability roadmap.
  • Build SDLC observability pipelines: Harness the APIs across the existing stack to collect, aggregate, and visualize engineering and quality telemetry.
  • Deliver self-service dashboards that give Engineering Managers and pod leads clear visibility into delivery efficiency and SDLC bottlenecks.
  • Define and enforce hard metrics: Establish and automate reporting for the Key Quality Indicators that objectively describe deployment health.
  • Create a quantifiable baseline for platform reliability using metrics such as Change Failure Rate, Deployment Frequency, Lead Time for Changes, Time to Restore, Regression Rate, Release Failure Rate, PR-failure rate, and code review depth.
  • Architect Shift-Left Pipeline Gates: Weave automated Performance, Security, and Accessibility checks directly into the CI/CD pipeline at the PR level in tight partnership with Eng Core.
  • Build Real-World Load Testing: Shift load and performance testing left for every customer onboarding, validating real-world assumptions using tools such as k6, Locust, Gatling, or JMeter.
  • Engineer Synthetic Data & Production Canaries: Build the architecture for safe synthetic data injection to unblock heavy load-testing and live-production canaries, strictly isolating test data from authentic user telemetry.
  • Leverage Generative AI Tooling: Actively utilize AI assistants to accelerate the development of testing frameworks, automate infrastructure code, and design advanced testing architectures.
  • Drive Tooling Consolidation: Lead the technical migration away from expensive, legacy testing infrastructure to a unified, AI-supported automation stack.
  • Maximize the value of existing platforms rather than introducing unnecessary vendor complexity.
  • Help define and maintain development practices.
  • Enable fast iteration while ensuring quality, including writing tests and documenting key implementations.

What they require

  • Comfort with regular early-morning or evening calls with colleagues in Hong Kong.
  • 5+ years of experience in software with proficiency in one or more common languages, and comfortable working across different technical systems and concerns.
  • Experience working at a systems level with modern developer infrastructure and production telemetry.
  • Ability to query, combine, and process data from tool APIs.
  • Experience building the mechanisms that make engineering health visible, not just consuming someone else's dashboard.
  • Experience personally instrumenting hard quality metrics — several of Change Failure Rate, Deployment Frequency, Lead Time for Changes, Time to Restore, Regression Rate, Release Failure Rate, PR-failure rate, code review depth, or SLIs/SLOs and error budgets.
  • Strong product-oriented mindset and care about outcomes over output.
  • Desire to understand the “why” behind what you build to connect your work to business impact.
  • Experience building and refactoring complex, often distributed, systems.
  • Experience with declarative infrastructure as code deployment patterns.
  • Experience with public cloud platforms such as GCP and/or AWS.
  • Hands-on experience with load and performance testing, or interest in building it.
  • Experience handling synthetic data safely so test traffic never contaminates real user telemetry.
  • AI experience in terms of testing tools and architecture.
  • Knowledge of how to build systems with AI agents as partners.
  • Clear strategies for strictly verifying and validating AI-generated code and infrastructure outputs before they merge.
  • Excellent communication and collaboration skills.
  • Ability to work effectively with cross-functional teams.
  • Ability to adapt quickly to new challenges and technologies.

Benefits

  • Competitive base salary.
  • Equity opportunities.
  • Performance-based bonus program.
  • Regular compensation reviews.
  • Comprehensive group medical coverage that includes coverage for hospitalization, outpatient care, optical services, and dental benefits.
  • No-Meeting Fridays.
  • Company holidays.
  • Access to mental health resources.
  • Generous annual leave policy.
  • Remote-first culture that supports collaboration and flexibility.
  • Learning programs.
  • Mentorship.
  • Professional development funding.
  • Regular performance feedback and reviews.
  • Reimbursement for office setup expenses.
  • Flexibility to work from home, enabling collaboration with global teams.
  • Paid parental leave for all new parents.
  • And much more!

Counterpart Health builds Counterpart Assistant, a clinically intuitive, AI-enabled solution that fits within physicians' workflows to help support earlier diagnosis and management of chronic conditions. Counterpart Health is a subsidiary of Clover Health.

HealthcareMid-size
CAD 115k–CAD 145k/yr