GridUnity

Lead and own quality engineering strategy and systems to ensure reliable, evidence-based release governance at scale. | 10+ years software engineering with leadership in quality initiatives, experience with automated testing systems, evidence-based release governance, AI-produced output, and CI/CD. | WHO WE ARE GridUnity is the industry leader in interconnection life cycle management, delivering cutting-edge software solutions that eliminate bottlenecks in the interconnection process and accelerate the transition to a more affordable, sustainable, and resilient energy future. Our Mission We unite all grid interconnection stakeholders on a single platform that converts centralized data into actionable intelligence and accelerates the transition to a reliable, sustainable, and cost-efficient electric grid. GridUnity is a trusted partner to leading utilities, grid operators, and policymakers. Our technology solutions tackle the interconnection queue backlog by significantly reducing processing times. Whether cutting transmission interconnection timelines from years to months or enabling distribution applications to be processed within a day, we help accelerate energy projects at every scale. Our Vision Energizing the planet with a faster, smarter, and more sustainable grid. What you'll do GridUnity spends its days removing bottlenecks from the interconnection queue. This role removes our bottlenecks. We are not hiring you to test our software. We are hiring you to build the system that makes "is this safe to ship" a fact we already have, not a meeting we still need. Being right and being fast pull against each other, and at our scale that tension is an engineering problem rather than a process one. As the Staff Software Engineer, Quality Engineering, you will own and lead GridUnity's quality engineering strategy: the technical vision and roadmap for the operating model as it scales, the standards it holds engineering to, and what counts as evidence that something is safe to ship. GridUnity engineering runs on an AI-native, artifact-first model. Agents draft tests from specs, run executions, and write automation. Humans arbitrate the evidence, own the release verdict, and continuously calibrate how much of the agents' judgment to trust. Version one of that system is live today on our flagship product line. You will take ownership of it, make it hold under real delivery pressure, and scale it across every product line. You will make quality a property of the engineering system itself: honest release gates, a defensible and deliberately shrinking catalog of human-judgment testing, and evaluation mechanisms that tell us exactly where human attention is needed. You report to the Director of Engineering Operations and partner closely with Product Engineering, Platform Engineering and DevOps to improve release confidence while accelerating delivery. Where we are, and where you come in Running now: the quality operating model is documented and live on our flagship product line. An agent-drafting workflow ships review-ready tests against documented why-manual criteria, enforced in the ticket lifecycle. A daily regression cadence runs green, with manual coverage held where human judgment is required. Evidence-backed release gating is live in our test-management system of record. An operations console harvests all of it nightly. Yours to build: making all of that hold under real delivery pressure, and taking it from the flagship line to the rest, and to the lines that do not exist yet. What you'll own • The release verdict, as a mechanism rather than a meeting. Execution records as evidence, exit criteria agreed before the deadline exists, a waiver path that blocks nobody but puts a name on the exception and counts it, and a defined escalation route, on the record, for the rare call those criteria do not cover. The mechanics exist; making them hold by design rather than by willpower is the work. • The agent pipeline. Operate and harden the system where agents generate, maintain, and run coverage across API, UI, integration, contract, performance and end-to-end, directly from specs and scenario contracts. Nothing becomes coverage until a person reviews and activates it, and you own where that bar sits. • The review loop. Drafts arrive continuously from engineers, product, and agents, and the review SLA is a promise to the whole company. Keeping it as agent output grows is a design problem, not a throughput one. • The shrinking catalog. Own the criteria for what stays human-tested, and build the demotion loop that retires manual tests as automation catches up. The first demotion pass is yours. • Calibration from zero. Stand up a corpus of golden human verdicts, score agent verdicts against it continuously, and use escape-rate data to point human attention where it actually pays. • Developer-owned quality. Push automated testing into the development lifecycle and the CI/CD pipelines so coverage runs where the code is written rather than in a lane beside it. • Behavioral validation as an external check. Persona walkthroughs, exploratory charters and judgment-based testing that verify behavior matches intent, not merely that the spec passed. This is the function that asks whether the spec was right. • The tooling call. Evaluate emerging testing technologies, agentic engineering practices and AI-assisted development tools, and decide which of them earn a place in how we work. The bar is whether something moves the evidence, not whether it is new. • The engineers around you. Mentor engineers and QA teammates through code review, pairing and technical design discussion, including the discipline of articulating why something is wrong precisely enough that the articulation becomes agent capability. The QA engineers are experienced, and we expect their technical judgment to be sharper for your being here. • The metrics that matter. Escape rate, verdict calibration, catalog trend, waiver frequency, deployment success, defined by you and used to argue. A note on the title "Software Engineer" comes first because that is the load-bearing skill. Our platform is largely TypeScript, and most of the code you review will have been written by an agent: fluently, confidently, and sometimes wrongly in ways only a strong engineer catches. "Quality Engineering" rather than "QA," because QA names a stage at the end of a process. We are asking you to make quality a property of the process itself: real exit criteria, evidence instead of assurances, and a manual test catalog that gets smaller each quarter. Not "SDET," the one we thought hardest about. SDET names a person whose deliverable is test code, and in our model agents write most of it. The scarce skill is no longer producing automation; it is deciding how much to believe what the automation reports, and knowing which tests have stopped earning their keep. If your best story is a framework you built, this probably is not your role. If it is the day you stopped trusting a green suite and could prove why, keep reading. What this job is not • Not running test execution. Experienced QA engineers own the daily cadence and keep it. You set the technical standard they work to. • Not building a Playwright suite. Framework depth is context for supervising agent output, not the deliverable. • Not release administration. If this role's answer to a risky release is to convene people, we have built the wrong thing. • Not AI research. The agents are already in production. They need to survive a deadline, not a demo. You might be the right person if • You have had to say a release was not ready when the date could not move. Afterwards you made sure the next call was settled by criteria agreed in advance, not by whoever argued hardest. • You have deleted test coverage on purpose and could defend it with data. • You have built an evaluation system of some kind, whether an eval harness, a labeling pipeline or scoring for model output, and you treat "can this judgment be trusted" as a measurement problem. • You ran automation at scale and concluded the real bottleneck was the operating model, not the coverage. • You get more out of changing how three teams work than out of being the most productive engineer in the room. What you'll bring Required • 10+ years across software engineering, quality engineering, or SDET work, including leading quality initiatives across multiple teams. • Real engineering ability: you can read, review, and harden agent-produced code and tests. Our platform is largely TypeScript. • Experience designing automated testing systems for enterprise SaaS, and the judgment to decide which testing belongs to machines and which belongs to people. • Experience with evidence-based release governance: gates, exit criteria, waivers, sign-off accountability, and the willingness to put your name on a verdict. • Experience building something around AI-produced output: agent-generated coverage, computer-use testing, LLM evaluation and calibration, or comparable. The specific shape matters less to us than having actually done it. • Depth in CI/CD, and in designing software that is testable by construction. • A track record of improving engineering organizations through influence rather than authority, including mentoring engineers more junior than you. Preferred • Built or transformed a quality engineering function at a high-growth SaaS company. • Prior Principal Engineer, Staff Engineer, Quality Engineering Architect, or senior SDET. • Shipped intelligent test generation, autonomous test maintenance, or agent-driven quality workflows to production. • Spec-driven or artifact-first development, where tests derive from executable contracts and scenario-level evidence is the closeout standard. • Test management operated as a system of record, Xray/Jira or comparable, where plans, executions, and traceability are evidence rather than paperwork. • Working knowledge of Playwright, Selenium, REST Assured, JUnit/TestNG, Cypress, or similar, as context for supervising agent-produced automation. • Distributed systems and cloud-native architecture depth: Kubernetes, serverless, microservices testing, and observability platforms used to improve production quality. OUR CULTURE We are a lean, fast-moving team that values bold thinking, reliability, and continuous learning. We operate with radical transparency, embrace scrappiness, and build solutions that anticipate customer needs. We also believe work should be fun and fulfilling — what we call “funfillment.” The right candidate is energized by working in a scaling, mission-driven company where they can shape processes, wear multiple hats, and grow alongside the business. BENEFITS/PERKS • Competitive compensation packages that recognize your expertise and contributions • Remote-first culture that provides flexibility and balance • Professional development opportunities, including training, mentorship, and career pathing • Comprehensive health, dental, and vision insurance starting day one • Short- and long-term disability and basic life insurance at no cost to you • 401(k) plan with a 4% match to help secure your future • Flexible PTO and a supportive work culture that values balance • Mission-driven work with the opportunity to make a significant impact in the energy sector ELIGIBILITY REQUIREMENT This position may involve access to data and systems subject to U.S. critical infrastructure protection regulations. Accordingly, this role is restricted to individuals who qualify as “U.S. persons,” defined by federal law as U.S. citizens, lawful permanent residents (green card holders), asylees, or refugees. OUR COMMITMENT TO APPLICANTS GridUnity is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, arrest and conviction record, or any other characteristic protected under applicable law. We are committed to creating an inclusive workplace where every team member feels valued, supported, and able to bring their authentic self to work. If you need a reasonable accommodation during the application or interview process, please email careers@gridunity.com. For your security, all official communication from GridUnity will only come from email addresses ending in @gridunity.com.

Lead and own quality engineering strategy and release governance for AI-driven automated testing systems. | 10+ years software engineering with leadership in quality initiatives, experience with automated testing systems, evidence-based release governance, AI-produced output, and CI/CD. | WHO WE ARE GridUnity is the industry leader in interconnection life cycle management, delivering cutting-edge software solutions that eliminate bottlenecks in the interconnection process and accelerate the transition to a more affordable, sustainable, and resilient energy future. Our Mission We unite all grid interconnection stakeholders on a single platform that converts centralized data into actionable intelligence and accelerates the transition to a reliable, sustainable, and cost-efficient electric grid. GridUnity is a trusted partner to leading utilities, grid operators, and policymakers. Our technology solutions tackle the interconnection queue backlog by significantly reducing processing times. Whether cutting transmission interconnection timelines from years to months or enabling distribution applications to be processed within a day, we help accelerate energy projects at every scale. Our Vision Energizing the planet with a faster, smarter, and more sustainable grid. What you'll do GridUnity spends its days removing bottlenecks from the interconnection queue. This role removes our bottlenecks. We are not hiring you to test our software. We are hiring you to build the system that makes "is this safe to ship" a fact we already have, not a meeting we still need. Being right and being fast pull against each other, and at our scale that tension is an engineering problem rather than a process one. As the Staff Software Engineer, Quality Engineering, you will own and lead GridUnity's quality engineering strategy: the technical vision and roadmap for the operating model as it scales, the standards it holds engineering to, and what counts as evidence that something is safe to ship. GridUnity engineering runs on an AI-native, artifact-first model. Agents draft tests from specs, run executions, and write automation. Humans arbitrate the evidence, own the release verdict, and continuously calibrate how much of the agents' judgment to trust. Version one of that system is live today on our flagship product line. You will take ownership of it, make it hold under real delivery pressure, and scale it across every product line. You will make quality a property of the engineering system itself: honest release gates, a defensible and deliberately shrinking catalog of human-judgment testing, and evaluation mechanisms that tell us exactly where human attention is needed. You report to the Director of Engineering Operations and partner closely with Product Engineering, Platform Engineering and DevOps to improve release confidence while accelerating delivery. Where we are, and where you come in Running now: the quality operating model is documented and live on our flagship product line. An agent-drafting workflow ships review-ready tests against documented why-manual criteria, enforced in the ticket lifecycle. A daily regression cadence runs green, with manual coverage held where human judgment is required. Evidence-backed release gating is live in our test-management system of record. An operations console harvests all of it nightly. Yours to build: making all of that hold under real delivery pressure, and taking it from the flagship line to the rest, and to the lines that do not exist yet. What you'll own • The release verdict, as a mechanism rather than a meeting. Execution records as evidence, exit criteria agreed before the deadline exists, a waiver path that blocks nobody but puts a name on the exception and counts it, and a defined escalation route, on the record, for the rare call those criteria do not cover. The mechanics exist; making them hold by design rather than by willpower is the work. • The agent pipeline. Operate and harden the system where agents generate, maintain, and run coverage across API, UI, integration, contract, performance and end-to-end, directly from specs and scenario contracts. Nothing becomes coverage until a person reviews and activates it, and you own where that bar sits. • The review loop. Drafts arrive continuously from engineers, product, and agents, and the review SLA is a promise to the whole company. Keeping it as agent output grows is a design problem, not a throughput one. • The shrinking catalog. Own the criteria for what stays human-tested, and build the demotion loop that retires manual tests as automation catches up. The first demotion pass is yours. • Calibration from zero. Stand up a corpus of golden human verdicts, score agent verdicts against it continuously, and use escape-rate data to point human attention where it actually pays. • Developer-owned quality. Push automated testing into the development lifecycle and the CI/CD pipelines so coverage runs where the code is written rather than in a lane beside it. • Behavioral validation as an external check. Persona walkthroughs, exploratory charters and judgment-based testing that verify behavior matches intent, not merely that the spec passed. This is the function that asks whether the spec was right. • The tooling call. Evaluate emerging testing technologies, agentic engineering practices and AI-assisted development tools, and decide which of them earn a place in how we work. The bar is whether something moves the evidence, not whether it is new. • The engineers around you. Mentor engineers and QA teammates through code review, pairing and technical design discussion, including the discipline of articulating why something is wrong precisely enough that the articulation becomes agent capability. The QA engineers are experienced, and we expect their technical judgment to be sharper for your being here. • The metrics that matter. Escape rate, verdict calibration, catalog trend, waiver frequency, deployment success, defined by you and used to argue. A note on the title "Software Engineer" comes first because that is the load-bearing skill. Our platform is largely TypeScript, and most of the code you review will have been written by an agent: fluently, confidently, and sometimes wrongly in ways only a strong engineer catches. "Quality Engineering" rather than "QA," because QA names a stage at the end of a process. We are asking you to make quality a property of the process itself: real exit criteria, evidence instead of assurances, and a manual test catalog that gets smaller each quarter. Not "SDET," the one we thought hardest about. SDET names a person whose deliverable is test code, and in our model agents write most of it. The scarce skill is no longer producing automation; it is deciding how much to believe what the automation reports, and knowing which tests have stopped earning their keep. If your best story is a framework you built, this probably is not your role. If it is the day you stopped trusting a green suite and could prove why, keep reading. What this job is not • Not running test execution. Experienced QA engineers own the daily cadence and keep it. You set the technical standard they work to. • Not building a Playwright suite. Framework depth is context for supervising agent output, not the deliverable. • Not release administration. If this role's answer to a risky release is to convene people, we have built the wrong thing. • Not AI research. The agents are already in production. They need to survive a deadline, not a demo. You might be the right person if • You have had to say a release was not ready when the date could not move. Afterwards you made sure the next call was settled by criteria agreed in advance, not by whoever argued hardest. • You have deleted test coverage on purpose and could defend it with data. • You have built an evaluation system of some kind, whether an eval harness, a labeling pipeline or scoring for model output, and you treat "can this judgment be trusted" as a measurement problem. • You ran automation at scale and concluded the real bottleneck was the operating model, not the coverage. • You get more out of changing how three teams work than out of being the most productive engineer in the room. What you'll bring Required • 10+ years across software engineering, quality engineering, or SDET work, including leading quality initiatives across multiple teams. • Real engineering ability: you can read, review, and harden agent-produced code and tests. Our platform is largely TypeScript. • Experience designing automated testing systems for enterprise SaaS, and the judgment to decide which testing belongs to machines and which belongs to people. • Experience with evidence-based release governance: gates, exit criteria, waivers, sign-off accountability, and the willingness to put your name on a verdict. • Experience building something around AI-produced output: agent-generated coverage, computer-use testing, LLM evaluation and calibration, or comparable. The specific shape matters less to us than having actually done it. • Depth in CI/CD, and in designing software that is testable by construction. • A track record of improving engineering organizations through influence rather than authority, including mentoring engineers more junior than you. Preferred • Built or transformed a quality engineering function at a high-growth SaaS company. • Prior Principal Engineer, Staff Engineer, Quality Engineering Architect, or senior SDET. • Shipped intelligent test generation, autonomous test maintenance, or agent-driven quality workflows to production. • Spec-driven or artifact-first development, where tests derive from executable contracts and scenario-level evidence is the closeout standard. • Test management operated as a system of record, Xray/Jira or comparable, where plans, executions, and traceability are evidence rather than paperwork. • Working knowledge of Playwright, Selenium, REST Assured, JUnit/TestNG, Cypress, or similar, as context for supervising agent-produced automation. • Distributed systems and cloud-native architecture depth: Kubernetes, serverless, microservices testing, and observability platforms used to improve production quality. OUR CULTURE We are a lean, fast-moving team that values bold thinking, reliability, and continuous learning. We operate with radical transparency, embrace scrappiness, and build solutions that anticipate customer needs. We also believe work should be fun and fulfilling — what we call “funfillment.” The right candidate is energized by working in a scaling, mission-driven company where they can shape processes, wear multiple hats, and grow alongside the business. BENEFITS/PERKS • Competitive compensation packages that recognize your expertise and contributions • Remote-first culture that provides flexibility and balance • Professional development opportunities, including training, mentorship, and career pathing • Comprehensive health, dental, and vision insurance starting day one • Short- and long-term disability and basic life insurance at no cost to you • 401(k) plan with a 4% match to help secure your future • Flexible PTO and a supportive work culture that values balance • Mission-driven work with the opportunity to make a significant impact in the energy sector ELIGIBILITY REQUIREMENT This position may involve access to data and systems subject to U.S. critical infrastructure protection regulations. Accordingly, this role is restricted to individuals who qualify as “U.S. persons,” defined by federal law as U.S. citizens, lawful permanent residents (green card holders), asylees, or refugees. OUR COMMITMENT TO APPLICANTS GridUnity is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, arrest and conviction record, or any other characteristic protected under applicable law. We are committed to creating an inclusive workplace where every team member feels valued, supported, and able to bring their authentic self to work. If you need a reasonable accommodation during the application or interview process, please email careers@gridunity.com. For your security, all official communication from GridUnity will only come from email addresses ending in @gridunity.com.

Lead and own quality engineering strategy and technical vision to ensure safe, evidence-based software releases using AI-driven testing automation. | 10+ years software or quality engineering experience, strong engineering ability in TypeScript, experience with automated testing systems and evidence-based release governance. | WHO WE ARE GridUnity is the industry leader in interconnection life cycle management, delivering cutting-edge software solutions that eliminate bottlenecks in the interconnection process and accelerate the transition to a more affordable, sustainable, and resilient energy future. Our Mission We unite all grid interconnection stakeholders on a single platform that converts centralized data into actionable intelligence and accelerates the transition to a reliable, sustainable, and cost-efficient electric grid. GridUnity is a trusted partner to leading utilities, grid operators, and policymakers. Our technology solutions tackle the interconnection queue backlog by significantly reducing processing times. Whether cutting transmission interconnection timelines from years to months or enabling distribution applications to be processed within a day, we help accelerate energy projects at every scale. Our Vision Energizing the planet with a faster, smarter, and more sustainable grid. What you'll do GridUnity spends its days removing bottlenecks from the interconnection queue. This role removes our bottlenecks. We are not hiring you to test our software. We are hiring you to build the system that makes "is this safe to ship" a fact we already have, not a meeting we still need. Being right and being fast pull against each other, and at our scale that tension is an engineering problem rather than a process one. As the Staff Software Engineer, Quality Engineering, you will own and lead GridUnity's quality engineering strategy: the technical vision and roadmap for the operating model as it scales, the standards it holds engineering to, and what counts as evidence that something is safe to ship. GridUnity engineering runs on an AI-native, artifact-first model. Agents draft tests from specs, run executions, and write automation. Humans arbitrate the evidence, own the release verdict, and continuously calibrate how much of the agents' judgment to trust. Version one of that system is live today on our flagship product line. You will take ownership of it, make it hold under real delivery pressure, and scale it across every product line. You will make quality a property of the engineering system itself: honest release gates, a defensible and deliberately shrinking catalog of human-judgment testing, and evaluation mechanisms that tell us exactly where human attention is needed. You report to the Director of Engineering Operations and partner closely with Product Engineering, Platform Engineering and DevOps to improve release confidence while accelerating delivery. Where we are, and where you come in Running now: the quality operating model is documented and live on our flagship product line. An agent-drafting workflow ships review-ready tests against documented why-manual criteria, enforced in the ticket lifecycle. A daily regression cadence runs green, with manual coverage held where human judgment is required. Evidence-backed release gating is live in our test-management system of record. An operations console harvests all of it nightly. Yours to build: making all of that hold under real delivery pressure, and taking it from the flagship line to the rest, and to the lines that do not exist yet. What you'll own • The release verdict, as a mechanism rather than a meeting. Execution records as evidence, exit criteria agreed before the deadline exists, a waiver path that blocks nobody but puts a name on the exception and counts it, and a defined escalation route, on the record, for the rare call those criteria do not cover. The mechanics exist; making them hold by design rather than by willpower is the work. • The agent pipeline. Operate and harden the system where agents generate, maintain, and run coverage across API, UI, integration, contract, performance and end-to-end, directly from specs and scenario contracts. Nothing becomes coverage until a person reviews and activates it, and you own where that bar sits. • The review loop. Drafts arrive continuously from engineers, product, and agents, and the review SLA is a promise to the whole company. Keeping it as agent output grows is a design problem, not a throughput one. • The shrinking catalog. Own the criteria for what stays human-tested, and build the demotion loop that retires manual tests as automation catches up. The first demotion pass is yours. • Calibration from zero. Stand up a corpus of golden human verdicts, score agent verdicts against it continuously, and use escape-rate data to point human attention where it actually pays. • Developer-owned quality. Push automated testing into the development lifecycle and the CI/CD pipelines so coverage runs where the code is written rather than in a lane beside it. • Behavioral validation as an external check. Persona walkthroughs, exploratory charters and judgment-based testing that verify behavior matches intent, not merely that the spec passed. This is the function that asks whether the spec was right. • The tooling call. Evaluate emerging testing technologies, agentic engineering practices and AI-assisted development tools, and decide which of them earn a place in how we work. The bar is whether something moves the evidence, not whether it is new. • The engineers around you. Mentor engineers and QA teammates through code review, pairing and technical design discussion, including the discipline of articulating why something is wrong precisely enough that the articulation becomes agent capability. The QA engineers are experienced, and we expect their technical judgment to be sharper for your being here. • The metrics that matter. Escape rate, verdict calibration, catalog trend, waiver frequency, deployment success, defined by you and used to argue. A note on the title "Software Engineer" comes first because that is the load-bearing skill. Our platform is largely TypeScript, and most of the code you review will have been written by an agent: fluently, confidently, and sometimes wrongly in ways only a strong engineer catches. "Quality Engineering" rather than "QA," because QA names a stage at the end of a process. We are asking you to make quality a property of the process itself: real exit criteria, evidence instead of assurances, and a manual test catalog that gets smaller each quarter. Not "SDET," the one we thought hardest about. SDET names a person whose deliverable is test code, and in our model agents write most of it. The scarce skill is no longer producing automation; it is deciding how much to believe what the automation reports, and knowing which tests have stopped earning their keep. If your best story is a framework you built, this probably is not your role. If it is the day you stopped trusting a green suite and could prove why, keep reading. What this job is not • Not running test execution. Experienced QA engineers own the daily cadence and keep it. You set the technical standard they work to. • Not building a Playwright suite. Framework depth is context for supervising agent output, not the deliverable. • Not release administration. If this role's answer to a risky release is to convene people, we have built the wrong thing. • Not AI research. The agents are already in production. They need to survive a deadline, not a demo. You might be the right person if • You have had to say a release was not ready when the date could not move. Afterwards you made sure the next call was settled by criteria agreed in advance, not by whoever argued hardest. • You have deleted test coverage on purpose and could defend it with data. • You have built an evaluation system of some kind, whether an eval harness, a labeling pipeline or scoring for model output, and you treat "can this judgment be trusted" as a measurement problem. • You ran automation at scale and concluded the real bottleneck was the operating model, not the coverage. • You get more out of changing how three teams work than out of being the most productive engineer in the room. What you'll bring Required • 10+ years across software engineering, quality engineering, or SDET work, including leading quality initiatives across multiple teams. • Real engineering ability: you can read, review, and harden agent-produced code and tests. Our platform is largely TypeScript. • Experience designing automated testing systems for enterprise SaaS, and the judgment to decide which testing belongs to machines and which belongs to people. • Experience with evidence-based release governance: gates, exit criteria, waivers, sign-off accountability, and the willingness to put your name on a verdict. • Experience building something around AI-produced output: agent-generated coverage, computer-use testing, LLM evaluation and calibration, or comparable. The specific shape matters less to us than having actually done it. • Depth in CI/CD, and in designing software that is testable by construction. • A track record of improving engineering organizations through influence rather than authority, including mentoring engineers more junior than you. Preferred • Built or transformed a quality engineering function at a high-growth SaaS company. • Prior Principal Engineer, Staff Engineer, Quality Engineering Architect, or senior SDET. • Shipped intelligent test generation, autonomous test maintenance, or agent-driven quality workflows to production. • Spec-driven or artifact-first development, where tests derive from executable contracts and scenario-level evidence is the closeout standard. • Test management operated as a system of record, Xray/Jira or comparable, where plans, executions, and traceability are evidence rather than paperwork. • Working knowledge of Playwright, Selenium, REST Assured, JUnit/TestNG, Cypress, or similar, as context for supervising agent-produced automation. • Distributed systems and cloud-native architecture depth: Kubernetes, serverless, microservices testing, and observability platforms used to improve production quality. OUR CULTURE We are a lean, fast-moving team that values bold thinking, reliability, and continuous learning. We operate with radical transparency, embrace scrappiness, and build solutions that anticipate customer needs. We also believe work should be fun and fulfilling — what we call “funfillment.” The right candidate is energized by working in a scaling, mission-driven company where they can shape processes, wear multiple hats, and grow alongside the business. BENEFITS/PERKS • Competitive compensation packages that recognize your expertise and contributions • Remote-first culture that provides flexibility and balance • Professional development opportunities, including training, mentorship, and career pathing • Comprehensive health, dental, and vision insurance starting day one • Short- and long-term disability and basic life insurance at no cost to you • 401(k) plan with a 4% match to help secure your future • Flexible PTO and a supportive work culture that values balance • Mission-driven work with the opportunity to make a significant impact in the energy sector ELIGIBILITY REQUIREMENT This position may involve access to data and systems subject to U.S. critical infrastructure protection regulations. Accordingly, this role is restricted to individuals who qualify as “U.S. persons,” defined by federal law as U.S. citizens, lawful permanent residents (green card holders), asylees, or refugees. OUR COMMITMENT TO APPLICANTS GridUnity is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, arrest and conviction record, or any other characteristic protected under applicable law. We are committed to creating an inclusive workplace where every team member feels valued, supported, and able to bring their authentic self to work. If you need a reasonable accommodation during the application or interview process, please email careers@gridunity.com. For your security, all official communication from GridUnity will only come from email addresses ending in @gridunity.com.

Lead and own quality engineering strategy and systems to ensure reliable, evidence-based release governance and scalable automated testing. | 10+ years software engineering with leadership in quality initiatives, strong TypeScript skills, experience with automated testing systems, evidence-based release governance, AI-produced output, and CI/CD expertise. | WHO WE ARE GridUnity is the industry leader in interconnection life cycle management, delivering cutting-edge software solutions that eliminate bottlenecks in the interconnection process and accelerate the transition to a more affordable, sustainable, and resilient energy future. Our Mission We unite all grid interconnection stakeholders on a single platform that converts centralized data into actionable intelligence and accelerates the transition to a reliable, sustainable, and cost-efficient electric grid. GridUnity is a trusted partner to leading utilities, grid operators, and policymakers. Our technology solutions tackle the interconnection queue backlog by significantly reducing processing times. Whether cutting transmission interconnection timelines from years to months or enabling distribution applications to be processed within a day, we help accelerate energy projects at every scale. Our Vision Energizing the planet with a faster, smarter, and more sustainable grid. What you'll do GridUnity spends its days removing bottlenecks from the interconnection queue. This role removes our bottlenecks. We are not hiring you to test our software. We are hiring you to build the system that makes "is this safe to ship" a fact we already have, not a meeting we still need. Being right and being fast pull against each other, and at our scale that tension is an engineering problem rather than a process one. As the Staff Software Engineer, Quality Engineering, you will own and lead GridUnity's quality engineering strategy: the technical vision and roadmap for the operating model as it scales, the standards it holds engineering to, and what counts as evidence that something is safe to ship. GridUnity engineering runs on an AI-native, artifact-first model. Agents draft tests from specs, run executions, and write automation. Humans arbitrate the evidence, own the release verdict, and continuously calibrate how much of the agents' judgment to trust. Version one of that system is live today on our flagship product line. You will take ownership of it, make it hold under real delivery pressure, and scale it across every product line. You will make quality a property of the engineering system itself: honest release gates, a defensible and deliberately shrinking catalog of human-judgment testing, and evaluation mechanisms that tell us exactly where human attention is needed. You report to the Director of Engineering Operations and partner closely with Product Engineering, Platform Engineering and DevOps to improve release confidence while accelerating delivery. Where we are, and where you come in Running now: the quality operating model is documented and live on our flagship product line. An agent-drafting workflow ships review-ready tests against documented why-manual criteria, enforced in the ticket lifecycle. A daily regression cadence runs green, with manual coverage held where human judgment is required. Evidence-backed release gating is live in our test-management system of record. An operations console harvests all of it nightly. Yours to build: making all of that hold under real delivery pressure, and taking it from the flagship line to the rest, and to the lines that do not exist yet. What you'll own • The release verdict, as a mechanism rather than a meeting. Execution records as evidence, exit criteria agreed before the deadline exists, a waiver path that blocks nobody but puts a name on the exception and counts it, and a defined escalation route, on the record, for the rare call those criteria do not cover. The mechanics exist; making them hold by design rather than by willpower is the work. • The agent pipeline. Operate and harden the system where agents generate, maintain, and run coverage across API, UI, integration, contract, performance and end-to-end, directly from specs and scenario contracts. Nothing becomes coverage until a person reviews and activates it, and you own where that bar sits. • The review loop. Drafts arrive continuously from engineers, product, and agents, and the review SLA is a promise to the whole company. Keeping it as agent output grows is a design problem, not a throughput one. • The shrinking catalog. Own the criteria for what stays human-tested, and build the demotion loop that retires manual tests as automation catches up. The first demotion pass is yours. • Calibration from zero. Stand up a corpus of golden human verdicts, score agent verdicts against it continuously, and use escape-rate data to point human attention where it actually pays. • Developer-owned quality. Push automated testing into the development lifecycle and the CI/CD pipelines so coverage runs where the code is written rather than in a lane beside it. • Behavioral validation as an external check. Persona walkthroughs, exploratory charters and judgment-based testing that verify behavior matches intent, not merely that the spec passed. This is the function that asks whether the spec was right. • The tooling call. Evaluate emerging testing technologies, agentic engineering practices and AI-assisted development tools, and decide which of them earn a place in how we work. The bar is whether something moves the evidence, not whether it is new. • The engineers around you. Mentor engineers and QA teammates through code review, pairing and technical design discussion, including the discipline of articulating why something is wrong precisely enough that the articulation becomes agent capability. The QA engineers are experienced, and we expect their technical judgment to be sharper for your being here. • The metrics that matter. Escape rate, verdict calibration, catalog trend, waiver frequency, deployment success, defined by you and used to argue. A note on the title "Software Engineer" comes first because that is the load-bearing skill. Our platform is largely TypeScript, and most of the code you review will have been written by an agent: fluently, confidently, and sometimes wrongly in ways only a strong engineer catches. "Quality Engineering" rather than "QA," because QA names a stage at the end of a process. We are asking you to make quality a property of the process itself: real exit criteria, evidence instead of assurances, and a manual test catalog that gets smaller each quarter. Not "SDET," the one we thought hardest about. SDET names a person whose deliverable is test code, and in our model agents write most of it. The scarce skill is no longer producing automation; it is deciding how much to believe what the automation reports, and knowing which tests have stopped earning their keep. If your best story is a framework you built, this probably is not your role. If it is the day you stopped trusting a green suite and could prove why, keep reading. What this job is not • Not running test execution. Experienced QA engineers own the daily cadence and keep it. You set the technical standard they work to. • Not building a Playwright suite. Framework depth is context for supervising agent output, not the deliverable. • Not release administration. If this role's answer to a risky release is to convene people, we have built the wrong thing. • Not AI research. The agents are already in production. They need to survive a deadline, not a demo. You might be the right person if • You have had to say a release was not ready when the date could not move. Afterwards you made sure the next call was settled by criteria agreed in advance, not by whoever argued hardest. • You have deleted test coverage on purpose and could defend it with data. • You have built an evaluation system of some kind, whether an eval harness, a labeling pipeline or scoring for model output, and you treat "can this judgment be trusted" as a measurement problem. • You ran automation at scale and concluded the real bottleneck was the operating model, not the coverage. • You get more out of changing how three teams work than out of being the most productive engineer in the room. What you'll bring Required • 10+ years across software engineering, quality engineering, or SDET work, including leading quality initiatives across multiple teams. • Real engineering ability: you can read, review, and harden agent-produced code and tests. Our platform is largely TypeScript. • Experience designing automated testing systems for enterprise SaaS, and the judgment to decide which testing belongs to machines and which belongs to people. • Experience with evidence-based release governance: gates, exit criteria, waivers, sign-off accountability, and the willingness to put your name on a verdict. • Experience building something around AI-produced output: agent-generated coverage, computer-use testing, LLM evaluation and calibration, or comparable. The specific shape matters less to us than having actually done it. • Depth in CI/CD, and in designing software that is testable by construction. • A track record of improving engineering organizations through influence rather than authority, including mentoring engineers more junior than you. Preferred • Built or transformed a quality engineering function at a high-growth SaaS company. • Prior Principal Engineer, Staff Engineer, Quality Engineering Architect, or senior SDET. • Shipped intelligent test generation, autonomous test maintenance, or agent-driven quality workflows to production. • Spec-driven or artifact-first development, where tests derive from executable contracts and scenario-level evidence is the closeout standard. • Test management operated as a system of record, Xray/Jira or comparable, where plans, executions, and traceability are evidence rather than paperwork. • Working knowledge of Playwright, Selenium, REST Assured, JUnit/TestNG, Cypress, or similar, as context for supervising agent-produced automation. • Distributed systems and cloud-native architecture depth: Kubernetes, serverless, microservices testing, and observability platforms used to improve production quality. OUR CULTURE We are a lean, fast-moving team that values bold thinking, reliability, and continuous learning. We operate with radical transparency, embrace scrappiness, and build solutions that anticipate customer needs. We also believe work should be fun and fulfilling — what we call “funfillment.” The right candidate is energized by working in a scaling, mission-driven company where they can shape processes, wear multiple hats, and grow alongside the business. BENEFITS/PERKS • Competitive compensation packages that recognize your expertise and contributions • Remote-first culture that provides flexibility and balance • Professional development opportunities, including training, mentorship, and career pathing • Comprehensive health, dental, and vision insurance starting day one • Short- and long-term disability and basic life insurance at no cost to you • 401(k) plan with a 4% match to help secure your future • Flexible PTO and a supportive work culture that values balance • Mission-driven work with the opportunity to make a significant impact in the energy sector ELIGIBILITY REQUIREMENT This position may involve access to data and systems subject to U.S. critical infrastructure protection regulations. Accordingly, this role is restricted to individuals who qualify as “U.S. persons,” defined by federal law as U.S. citizens, lawful permanent residents (green card holders), asylees, or refugees. OUR COMMITMENT TO APPLICANTS GridUnity is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, arrest and conviction record, or any other characteristic protected under applicable law. We are committed to creating an inclusive workplace where every team member feels valued, supported, and able to bring their authentic self to work. If you need a reasonable accommodation during the application or interview process, please email careers@gridunity.com. For your security, all official communication from GridUnity will only come from email addresses ending in @gridunity.com.

Lead and own quality engineering strategy and systems for AI-assisted test coverage and release governance. | 10+ years software engineering with leadership in quality engineering, experience with AI-assisted testing workflows, strong software engineering skills, and ability to influence engineering strategy. | WHO WE ARE GridUnity is the industry leader in interconnection life cycle management, delivering cutting-edge software solutions that eliminate bottlenecks in the interconnection process and accelerate the transition to a more affordable, sustainable, and resilient energy future. Our Mission We unite all grid interconnection stakeholders on a single platform that converts centralized data into actionable intelligence and accelerates the transition to a reliable, sustainable, and cost-efficient electric grid. GridUnity is a trusted partner to leading utilities, grid operators, and policymakers. Our technology solutions tackle the interconnection queue backlog by significantly reducing processing times. Whether cutting transmission interconnection timelines from years to months or enabling distribution applications to be processed within a day, we help accelerate energy projects at every scale. Our Vision Energizing the planet with a faster, smarter, and more sustainable grid. What You'll Do As the Staff Software Engineer, Quality Engineering, you will own and lead GridUnity's quality engineering strategy. GridUnity engineering operates on an AI-native, artifact-first development model: AI agents draft tests, run executions, and write automation, while humans arbitrate evidence, own release verdicts, and continuously calibrate agent judgment. Version one of that quality system is live today for our flagship product line: agents draft manual tests from feature specs and stories through a gated workflow with documented why-manual criteria; QA reviews and activates them; releases run through evidence-backed gates in our test-management system of record; and a quality operations console harvests it all nightly. You will take ownership of that system, make it hold under real delivery pressure, and scale it across every product line. This is not a traditional QA role, and it is not a traditional test-automation role either. You will serve as a technical leader, architect, and change agent who makes quality a property of the engineering system itself: honest release gates, a defensible (and deliberately shrinking) catalog of human-judgment testing, and evaluation mechanisms that tell us exactly where human attention is needed. The mechanisms exist; the discipline is young. Some of the hardest parts - keeping review throughput inside its SLA, making gates stick under deadline pressure, retiring manual tests as automation catches up - are exactly where you will earn your impact. Reporting within Engineering Operations, you'll partner closely with Product Engineering, Platform Engineering, and DevOps to improve release confidence while accelerating delivery. You will: • Own the quality operating model - currently live for our flagship product line - and lead its expansion across the organization's product lines, evolving the technical vision and roadmap as it scales. • Operate and harden the pipeline in which agents generate, maintain, and execute test coverage - API, UI, integration, contract, performance, and end-to-end - directly from feature specs and scenario contracts, with human review and activation workflows that keep the coverage trustworthy. • Run the review-and-activation loop: drafts arrive continuously from engineers, product, and agents, and the review SLA is a promise to the whole organization - you keep throughput honest and the draft queue moving. • Own the release-gate discipline: execution records as evidence, explicit exit criteria, named waivers, evidence-backed sign-off, and escalation paths. The gate mechanics are built; making them hold under deadline pressure - every release, no silent exceptions - is the job. • Steward the criteria for what remains human-tested, and stand up the demotion loop that retires manual tests as automation capability catches up - a shrinking manual catalog is a success metric, not a loss. The first demotion pass will be yours to run. • Build the evaluation discipline for agent-driven quality from the ground up: establish a calibration corpus of golden human verdicts, continuously score agent verdicts against it, and use escape-rate data to steer where human review effort is concentrated. • Champion developer-owned quality by embedding automated testing into the software development lifecycle and CI/CD pipelines. • Advance behavioral validation as an external evaluation function - persona walkthroughs, exploratory charters, and judgment-based testing that verify behavior matches intent, not merely that specs pass. • Partner with Engineering Managers and Staff Engineers to improve software reliability, maintainability, and developer productivity. • Mentor engineers and QA teammates through code reviews, pairing sessions, and technical design discussions - including the discipline of articulating why something is wrong precisely enough that the articulation becomes agent capability. • Define engineering quality metrics - escape rate, agent-verdict calibration, catalog trends, waiver frequency, deployment success - and use data to continuously improve software reliability and customer experience. • Evaluate emerging testing technologies, agentic engineering practices, and AI-assisted development tools to continuously evolve GridUnity's engineering capabilities. • Serve as a technical thought leader, influencing engineering strategy and helping establish a culture where agents generate coverage, humans arbitrate evidence, and quality is engineered - not inspected. Where the system stands today We believe candor about the starting point matters for a role like this. What's already running: the quality operating model is documented and live for our flagship product line; an agent-drafting workflow ships review-ready manual tests against documented why-manual criteria, enforced in the ticket lifecycle; a daily manual regression cadence is green; the first evidence-backed release gate is stood up in our test-management system of record; and an operations console harvests and renders all of it nightly. What's next and yours: driving review throughput to its SLA, making gate discipline stick through real release deadlines, running the first demotion pass on the manual catalog, building the agent-verdict calibration corpus from zero, and taking the model from one product line to all of them. What You'll Bring Required Knowledge, Skills, and Abilities • 10+ years of experience in Software Engineering, Quality Engineering, or Software Development Engineer in Test (SDET) roles, including experience leading quality engineering initiatives across multiple engineering teams. • Experience designing agentic or AI-assisted quality workflows: agent-generated test coverage, computer-use testing, LLM evaluation and calibration, or comparable systems built around AI-produced output. • Proven experience designing modern automated testing systems for enterprise SaaS applications - and the judgment to decide which testing work belongs to machines versus humans. • Strong software engineering skills, including the ability to read, review, and harden agent-produced code and tests (our platform is largely Java and TypeScript). • Experience with evidence-based release governance: release gates, exit criteria, waivers, and sign-off accountability - and the willingness to put your name on a verdict. • Deep understanding of distributed systems, cloud-native applications, CI/CD, and designing highly testable software architectures. • Demonstrated experience improving engineering organizations through technical leadership, mentoring, and influence. • Excellent communication skills with the ability to influence technical direction across multiple engineering teams. • Passion for developer experience, engineering enablement, and continuous improvement. Preferred Knowledge, Skills, and Abilities • Experience building or transforming a Quality Engineering organization in a high-growth SaaS company. • Previous experience as a Principal Engineer, Staff Engineer, Quality Engineering Architect, or senior SDET. • Experience shipping intelligent test generation, autonomous test maintenance, or agent-driven quality workflows in production. • Working knowledge of common automation technologies (Playwright, Selenium, REST Assured, JUnit/TestNG, Cypress, or comparable) - as context for supervising and evolving agent-produced automation. • Experience implementing developer-owned quality, shift-left testing, testing pyramid strategies, and engineering quality metrics. • Experience with spec-driven or artifact-first development practices - testing derived from executable contracts, with scenario-level evidence as the closeout standard. • Experience operating test management as a system of record (Xray/Jira or comparable) - plans, executions, and traceability treated as evidence, not paperwork. • Familiarity with cloud-native platforms, Kubernetes, serverless architectures, and microservices testing. • Experience leveraging observability platforms to improve production quality and release confidence. OUR CULTURE We are a lean, fast-moving team that values bold thinking, reliability, and continuous learning. We operate with radical transparency, embrace scrappiness, and build solutions that anticipate customer needs. We also believe work should be fun and fulfilling — what we call “funfillment.” The right candidate is energized by working in a scaling, mission-driven company where they can shape processes, wear multiple hats, and grow alongside the business. BENEFITS/PERKS • Competitive compensation packages that recognize your expertise and contributions • Remote-first culture that provides flexibility and balance • Professional development opportunities, including training, mentorship, and career pathing • Comprehensive health, dental, and vision insurance starting day one • Short- and long-term disability and basic life insurance at no cost to you • 401(k) plan with a 4% match to help secure your future • Flexible PTO and a supportive work culture that values balance • Mission-driven work with the opportunity to make a significant impact in the energy sector ELIGIBILITY REQUIREMENT This position may involve access to data and systems subject to U.S. critical infrastructure protection regulations. Accordingly, this role is restricted to individuals who qualify as “U.S. persons,” defined by federal law as U.S. citizens, lawful permanent residents (green card holders), asylees, or refugees. OUR COMMITMENT TO APPLICANTS GridUnity is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, arrest and conviction record, or any other characteristic protected under applicable law. We are committed to creating an inclusive workplace where every team member feels valued, supported, and able to bring their authentic self to work. If you need a reasonable accommodation during the application or interview process, please email careers@gridunity.com. For your security, all official communication from GridUnity will only come from email addresses ending in @gridunity.com.