Microgrid Validation Engineer

About the role

We’re a team of friends bound together by a mission to preserve our planet for future generations through innovative energy solutions and modern infrastructure. Intersect develops, constructs, and operates the most ambitious power and data center infrastructure in the country by co-locating industrial demand with dedicated gas and renewable power generation. Intersect was acquired by Google in March 2026 and operates as an independent subsidiary. We are developing and constructing multiple gigawatts of energy and data center projects in the U.S., enabling more data center and generation capacity to come online faster. We’re on an aggressive growth trajectory and looking for people hungry to tackle the largest energy challenges on the planet. Location & Team Gatherings: We are currently looking for candidates located within 60 miles of any of the listed location. We connect as a team at our Team Week experiences four times a year and at our recently established Hub locations - SF Bay Area, NYC Metro Area, NY; Denver, CO; Austin, TX; Calgary, AB; and Toronto, ON.

Responsibilities

• Build Validation Frameworks and Test Automation: Develop software validation tools and simulation frameworks that exercise control algorithms across a full range of operating conditions, including failure modes, communication delays, and equipment faults.
• Design and maintain automated test execution workflows that improve validation efficiency, repeatability, and reporting.
• Create scalable validation processes that support the continued growth and deployment of microgrid systems.
• Define Test Cases and Performance Criteria: Partner with controls engineers, power systems engineers, utilities, and external stakeholders to define validation scenarios, test cases, and performance requirements.
• Verify controller behavior under both normal operating conditions and abnormal system events.
• Establish objective performance metrics and acceptance criteria to evaluate system readiness.
• Integrate Field Learnings into Validation: Analyze field operating data to improve simulation fidelity and identify previously untested edge cases.
• Incorporate operational insights into regression test suites to continuously strengthen validation coverage.
• Support root-cause investigations