Software Developer - Engineering Productivity

Accountabilities:
Design and implement internal engineering productivity initiatives that improve software quality, reliability, and development efficiency across engineering teams. Build and maintain SDLC observability solutions by integrating data from engineering tools, APIs, and platforms to provide actionable insights into delivery performance. Develop dashboards and reporting systems that measure key engineering health indicators, including deployment frequency, change failure rate, lead time, recovery time, regression rates, and release quality. Architect and implement automated quality gates within CI/CD pipelines, incorporating performance, security, accessibility, and reliability checks. Create scalable load testing strategies using tools such as k6, Locust, Gatling, or JMeter to validate system performance and customer readiness. Develop safe synthetic data solutions and production canary approaches to support testing while protecting real user data and telemetry. Leverage AI-powered development tools to accelerate engineering workflows, automate repetitive tasks, and improve testing and infrastructure processes. Drive improvements to engineering tooling by consolidating platforms, reducing unnecessary complexity, and maximizing existing technology investments. Collaborate with engineering teams to define development best practices, improve documentation, and promote reliable software delivery practices. Act as a reliability advocate by identifying improvement opportunities, reducing technical friction, and enabling teams to deliver higher-quality software. Requirements: 5+ years of software engineering experience with proficiency in one or more programming languages such as Python or Go. Experience working with developer infrastructure, platform engineering, production telemetry, and engineering systems at scale. Strong ability to integrate, query, and analyze data from engineering tools and APIs such as GitHub, Linear, cloud platforms, monitoring tools, or equivalent technologies. Hands-on experience establishing engineering metrics, reliability indicators, SLIs/SLOs, error budgets, or software delivery analytics. Strong understanding of distributed systems, infrastructure automation, and declarative Infrastructure as Code (IaC) practices. Experience working with cloud platforms such as GCP, AWS, or similar environments. Familiarity with load testing, performance engineering, synthetic data generation, and safe testing practices. Experience using AI development tools such as Gemini, Claude, Cursor, Codex, or similar technologies to enhance engineering workflows. Ability to evaluate and validate AI-generated code, infrastructure changes, and automated solutions before production use. Product-oriented mindset with the ability to understand business objectives and connect technical solutions to measurable outcomes. Excellent communication and collaboration skills with the ability to work effectively across globally distributed teams. Ability to adapt quickly, solve complex problems, and continuously improve engineering processes. Benefits: Competitive base salary range of approximately CAD $115,000 - $145,000, depending on experience, skills, and market factors. Equity opportunities and performance-based bonus programs. Regular compensation reviews to recognize impact and contributions. Comprehensive medical coverage, including hospitalization, outpatient care, vision, and dental benefits. Remote-first work environment with flexibility to work from home. Support for global collaboration and distributed teamwork. Paid parental leave for all new parents. Generous annual leave policy, company holidays, and wellness initiatives. No-Meeting Fridays to support focus time and work-life balance. Access to mental health resources and employee well-being programs. Professional development funding, mentorship opportunities, learning programs, and career growth support. Reimbursement for home office setup expenses. A collaborative environment focused on innovation, inclusion, and meaningful impact.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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