Senior Software Quality Engineer

SkySpecs

13d•$120,000 - $15,000•Hybrid

About The Position

As a Senior Software Quality Engineer, you will help shape the future of our Horizon platform and the way we build software. Horizon is the platform behind SkySpecs' wind and solar inspection and asset-management business, and the work is hands-on building, end to end. As the cost of producing code falls, an engineer's impact comes more than ever from judgment, design, and outcomes, not volume. AI is central to how we work here, and we treat it as serious leverage: a force multiplier for engineers who already have strong instincts, not a substitute for them. We expect everyone to keep pushing what AI, automation, and agents make possible, and to bring the judgment that makes that leverage pay off. We think about quality as a platform discipline, not a gate in the development process. Software Engineers own the quality of the software they build. Software Quality Engineers build the platform, tooling, automation, and feedback systems that enable engineering teams to ship software with confidence. Software Quality Engineers help ensure software is not only testable, but also observable and measurable from the moment it is specified. Our platform is built using AWS, GitLab, Auth0, Grafana, Terraform, Kafka, Node.js, TypeScript, Apollo GraphQL, React, Ant Design, and PostgreSQL. Our test suite includes Pytest, Vitest, and Playwright.

Requirements

5+ years building and maintaining quality platforms, automated testing systems, developer tooling, or similar engineering systems for production software.
Strong software engineering fundamentals and systems-thinking.
Deep understanding of software quality across testing, observability, application performance, and production systems.
Experience designing and maintaining automated testing frameworks, quality infrastructure, CI/CD quality gates, and engineering feedback systems.
Experience developing and maintaining automated quality solutions across frontend applications, backend services, APIs, and production systems.
Experience using production telemetry, application performance monitoring, session replay, or similar tools to identify and prioritize quality improvements.
Ability to independently drive quality initiatives from concept through implementation.
Strong written communication skills.
Demonstrated ability to work within a cross-functional team of technical and non-technical contributors.
Hands-on experience with AI-assisted and agentic development workflows, and a track record of evolving how you use them.
Sound judgment when using AI tools, including reviewing and correcting agent-generated tests and code.

Nice To Haves

Familiarity with our stack: AWS, GitLab, Auth0, Grafana, Terraform, Kafka, Node.js, TypeScript, Apollo GraphQL, React, Ant Design, Vitest, Playwright, and PostgreSQL.
Experience building internal engineering platforms, developer tooling, observability platforms, or quality platforms.
Experience improving CI/CD pipelines and release engineering.
Experience operating distributed systems at scale.
Background in utility-scale energy generation, with an emphasis on renewables.

Responsibilities

Build and evolve our quality platform. Examples include: Building and maintaining quality infrastructure, automation, and developer tooling. Building tooling that enables Software Engineers to write, execute, and maintain effective tests. Improving CI/CD quality gates and release confidence. Building and maintaining application quality telemetry, dashboards, and alerting. Integrating quality signals from testing, production telemetry, application performance, and user behavior into engineering workflows. Leveraging AI tools and autonomous agents to accelerate quality engineering.
Partner on solution design and quality strategy. Examples include: Participating in specification, feature design, and implementation planning. Helping define clear, testable, observable, and measurable acceptance criteria. Identifying quality risks and opportunities to improve testability. Designing high-signal testing strategies across unit, integration, end-to-end, and production environments. Using production telemetry, application performance metrics, and session recordings to identify user friction, regressions, and opportunities to improve future designs. Coaching Software Engineers on effective testing, observability, and quality practices. Reviewing implementation plans, testing approaches, and AI-generated tests.
Improve Horizon, our engineering systems, and the way we work. Examples include: Continuously improving how we measure user experience, application performance, and release health. Analyzing production issues and strengthening our quality systems. Building feedback loops that help engineering teams identify regressions before customers report them. Exploring new ideas, experiments, and prototypes that could improve Horizon or the way we build software. Expanding AI and agent capabilities. Reducing operational toil through automation.