About Build Build is creating the agentic AI stack for the built world. We help institutional real estate teams automate complex development and acquisitions workflows so important projects can move from concept to completion faster, with less cost, delay, and operational drag. Our customers include some of the largest built-world institutions: alternative asset investors, developers, infrastructure owners, energy companies, industrial operators, and public-sector partners. Their work shapes the physical world, but the workflows behind that work are still slow, fragmented, document-heavy, and dependent on expert coordination. We believe the next generation of built-world software will not just organize work. It will help do the work. Agents will reason across documents, drawings, financial models, market data, approvals, constraints, and expert judgment. Human experts will stay in control, but they will operate with far more leverage. We are backed by leading investors and operators, including executives from Blackstone and OpenAI, alongside top venture firms. We are building a generational company at the intersection of AI and the physical world. About the role The data center build-out is the defining infrastructure challenge of this decade. Every hyperscaler, every operator, every institutional developer is constrained by one thing above all others: power. Getting it, connecting it, planning around it, and moving fast enough to matter. Build pairs agentic AI with deep domain expertise to deliver the work that used to take weeks in hours. We work with some of the largest infrastructure investors, developers, and operators in the world. Our domain experts are the reason the outputs are trusted. "The AI does the work. The domain expert makes it right." This role is for someone who has spent years inside the grid — not studying it, operating it. Transmission planning, real-time dispatch, SCADA, contingency analysis, power flow studies. You understand why decisions get made the way they do, and you can explain it clearly to people who are moving fast and need to get it right. You'll review, validate, and steer AI-generated work across live client engagements. You'll help define what good judgment looks like in practice. And you'll be part of a small, high-output team doing work that actually moves the needle on how the world's most important infrastructure gets built. What you'll do Review and validate AI-generated energy systems work — contingency assessments, power flow studies, interconnection analysis, capacity planning Apply practitioner judgment to real client problems: what's physically feasible, what the trade-offs are, and where the AI got it wrong Collaborate with Build's engineering and domain teams to improve workflow accuracy and output quality over time Produce operational analyses, planning scenarios, and written assessments where needed Help articulate what "correct" looks like — the assumptions, constraints, and engineering realities that aren't in any textbook Domain focus Build's grid and energy engagements span the full stack of what institutional infrastructure clients need: Grid planning and optimization — OPF, N-1/N-2 contingency screening, load flow studies, renewable integration Power availability and interconnection — site-level power assessment, grid connection feasibility, capacity analysis Data and process workflows — historian data, compliance documentation, audit trail interpretation Regulatory and standards environments — NERC CIP, TSO/ISO operating frameworks, utility compliance Tools our clients and workflows operate around include PSS/E, PowerWorld, MATPOWER, and OpenDSS. You don't need to know all of them — but you should be comfortable with the environments they represent. What we're looking for 5+ years of hands-on experience in transmission planning, power systems engineering, or utility systems — at a TSO, ISO, or large utility The ability to explain why a decision is correct, not just produce it — trade-offs, constraints, physical limits Clear, direct written communication. Our workflows are asynchronous and our clients move fast. Comfort working with AI-generated outputs and improving them — not just reviewing from a distance Preference for flexible, contract-based engagements over traditional employment How it works Fully remote, contract-based Engagements vary in scope and duration — some short-term, some ongoing retainers Hourly rate: $75–$200 depending on experience and scope. Exceptional expertise goes higher. Ongoing collaborations structured as monthly retainers where volume justifies it Assessment: CV review and a paid work sample if there's a fit