Software Engineer, Energy Sales Platform ($175k - $235k + equity) at Gridmatic

Who We're Hiring For: Gridmatic, an energy company that uses ML forecasting and optimization to trade renewable energy and operate grid-scale batteries profitably. Role Snapshot: Software Engineer on the Energy Sales Platform, building the automation that lets Gridmatic sign large industrial energy customers without scaling a traditional sales team. Compensation: $175k - $235k base + equity What This Role Is About: Gridmatic grew energy sales roughly 100x in the last 18 months and wants to 10x again to become a gigawatt-scale retailer. You'll build the platform that automates pricing, usage forecasting, and contracting for large industrial customers like datacenters and flexible loads. Incumbent energy companies need hundreds of salespeople to do this; Gridmatic wants to do it with fewer than ten. What Makes This Opportunity Exceptional: Gridmatic is the most profitable participant in ERCOT's wholesale market and operates the top-performing battery asset in CAISO, all without venture capital funding. Energy sales grew 100x in 18 months. The next target is gigawatt-scale retail, which would put Gridmatic among the leading renewable energy companies. A 50-person company where engineers own full product slices end-to-end, from data modeling through frontend, with direct impact on revenue. What You'll Be Responsible For: Build deep automation for pricing, forecasting, and contracting, including using AI to price from unstructured emails, processing large-scale timeseries usage data, and modeling complex customer contracts. Expand into new energy markets by integrating new utilities, datasets, and pricing rules so the sales platform works across regions. Work directly with energy domain experts to define what to build, gather requirements, and ship iteratively against real customer needs. Who Will Thrive in This Role: You build product end-to-end (spec, data model, backend, frontend, design) and are comfortable owning the full stack rather than waiting for handoffs. You're good with messy, large-scale data. Energy data is inconsistent and complex. You need to design schemas, write queries, and make sense of it without clean documentation. You operate well in ambiguity. Priorities shift, specs are incomplete, and you'll need to manage your own focus in a fast-moving startup with a small team. #J-18808-Ljbffr Standout