Software Developer - Engineering Productivity
C
Counterpart HealthHealth Tech
Remote - Canada, Global distribution requires regular early-morning or evening calls to coordinate with teams in Hong Kong.Full-TimeSenior
Salary115,000 CAD to 145,000 CAD
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonGCPGoCI/CDGenerative AI
Requirements
- 5+ years of software experience with proficiency in one or more common languages (e.g., Python, Go).
- Experience at a systems level with modern developer infrastructure and production telemetry.
- Proven ability to query, combine, and process data from tool APIs (e.g., GitHub, Linear, GCP, Sentry, Grafana, incident.io).
- Demonstrated experience instrumenting hard quality metrics such as Change Failure Rate, Deployment Frequency, or SLIs/SLOs.
- Experience building and refactoring complex, distributed systems.
- Proficiency with declarative infrastructure as code (IaC) deployment patterns.
- Experience with public cloud platforms such as GCP and/or AWS.
- Hands-on experience with load and performance testing (k6, Locust, Gatling, or JMeter).
- Experience utilizing AI assistants for testing architecture and code generation.
- Strong product-oriented mindset with the ability to connect work to business impact.
- Excellent communication and collaboration skills for cross-functional teamwork.
Responsibilities
- Drive engineering-wide process changes and reliability standards adoption.
- Build and visualize SDLC observability pipelines using stack APIs (GitHub, Linear, GCP, Sentry, Grafana, incident.io).
- Define and automate reporting for Key Quality Indicators (e.g., Change Failure Rate, Deployment Frequency).
- Architect shift-left pipeline gates integrating performance, security, and accessibility checks.
- Implement real-world load testing using tools like k6, Locust, Gatling, or JMeter.
- Develop architecture for synthetic data injection and production canaries.
- Leverage generative AI tooling to accelerate testing framework and infrastructure automation.
- Lead migration from legacy testing infrastructure to a unified, AI-supported automation stack.
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