AGent Energy is building a leading software platform to optimize distributed generation resources. They are seeking a skilled Quality Assurance Engineer to own testing and quality across their technology stack, ensuring reliability in their energy platform through comprehensive test strategies and cross-functional collaboration.
Responsibilities:
- Design, build, and maintain comprehensive test strategies that cover the full AGent platform — cloud backend, IoT device communication, embedded firmware, and customer-facing application layers
- Develop and execute functional, integration, regression, and end-to-end test suites across all platform components
- Own test planning for new features and releases, working closely with engineering leads to ensure quality is built in from the start — not bolted on at the end
- Maintain clear documentation of test coverage, results, and known issues across the platform
- Test AWS infrastructure components including IoT Core device provisioning, Lambda functions, and data ingestion pipelines
- Validate TimescaleDB schema performance and data integrity under high-volume, high-frequency telemetry loads
- Test API integrations, data pipelines, and backend services for reliability, accuracy, and performance at scale
- Develop and execute test protocols for IoT device communication, provisioning workflows, and command handling between cloud and embedded systems
- Partner with the Embedded Engineering team to validate firmware behavior, device-to-cloud messaging, and real-time control event accuracy
- Build test environments and simulation frameworks that replicate real-world generator behavior and edge conditions
- Build and maintain automated test suites integrated into AGent's CI/CD pipelines via GitHub Actions
- Implement automated regression coverage that catches issues before they reach production
- Continuously improve test efficiency, coverage, and reliability through automation and tooling
- Partner with Cloud Backend, Application, and Embedded Engineering teams throughout the development lifecycle — not just at the end
- Identify, document, and track bugs with clear reproduction steps and prioritization recommendations
- Contribute to post-incident reviews and help drive process improvements that prevent recurrence
- Actively use Claude AI and other AI tools to accelerate test case generation, documentation, and defect analysis — and bring a continuous improvement mindset to how AI can raise quality across the team
Requirements:
- 3–5 years of QA engineering experience with demonstrated ownership of end-to-end test strategy and execution
- Hands-on experience testing cloud-based systems — AWS experience strongly preferred
- Familiarity with IoT systems, device communication protocols, and embedded or firmware testing
- Experience building and maintaining automated test frameworks and integrating them into CI/CD pipelines
- Strong SQL skills for data validation and backend testing
- Experience with Claude AI or other AI tools in a professional context, or a demonstrated eagerness to integrate AI into your QA workflow
- Detail-oriented with strong written communication skills — you document clearly and advocate for quality convincingly
- Ability to work cross-functionally across cloud, embedded, and application engineering teams
- Experience testing mission-critical or real-time industrial systems where reliability requirements are non-negotiable
- Familiarity with time-series databases (TimescaleDB or similar) and high-volume data pipeline testing
- Exposure to distributed energy resources, generator technologies, backup power systems (big plus!), or grid-edge infrastructure
- Experience with performance and load testing at scale
- Proficiency with Python or .NET (C#) for test automation