About the role
Company Description Palmetto is a leading clean tech company on a mission to accelerate the transition to a clean energy future. With a belief that consumers can have it all, we are an uncompromising energy company that makes coming clean a no brainer. Our award-winning technology platform empowers homeowners, businesses, and entrepreneurs to adopt renewable energy through simple, scalable, and innovative solutions. Operating at the intersection of B2B and D2C, we offer software, financial products, and services that drive real environmental impact—without compromising value. We deliver end-to-end solutions for whole home electrification that put clean energy within reach for all. Our employees are our most valuable resource. We foster a promote-from-within culture that prioritizes talent development, career growth, and purpose-driven work. Palmetto offers a comprehensive
benefits package—including unlimited PTO, medical, dental, and vision coverage, paid parental leave, retirement plans, and more—so you can have it all both personally and professionally. Palmetto prioritizes people, planet, and profit—backed by a culture that values collaboration, impact, and balance. Join us in building a brighter, cleaner world. Location This position will be based in Charlotte, NC, New York, NY or Boston, MA. Reporting This position will report to the Director of Engineering, Building Science Summary of Role Come build the software and data layer that helps make energy cleaner and cheaper for millions of homes: turning fragmented, real-world energy data into structured, trustworthy intelligence that our products, customers, and partners can act on. You'll develop the services, pipelines, and models that estimate how homes use, produce, and pay for energy, and run them as reliable production APIs at scale.
The role spans physics-based and machine-learning energy modeling, large-scale geospatial and remote-sensing data processing, utility and grid data processing across every US market, and AI systems where LLM-powered agents extract data from complex source documents with humans in the loop. We're looking for a strong, versatile engineer, comfortable across frontend, backend, and the underlying infrastructure, and who is fluent with modern AI frameworks, tooling, and harnesses. This role sits in the Data and Energy Intelligence Unit, a multidisciplinary team of engineers and scientists owning data-intensive applications across energy modeling, geospatial data, and applied AI. Energy expertise is a plus, but we care most about excellent engineering and sound judgment; the domain is something a strong, curious engineer can learn on the job. Strategic & Tactical Build and ship features end-to-end across the stack, from production APIs and data pipelines to the interfaces on top of them. Develop AI-powered capabilities where they fit, including LLM- and agent-based systems that extract structured, validated data from complex, unstructured documents with a human-in-the-loop review workflow. Take models from prototype to production: build the APIs, pipelines, and infrastructure that run physics-based and machine-learning models reliably at scale, with the testing and observability needed to catch regressions before they reach customers. Work with large geospatial and remote-sensing datasets (imagery, elevation, and related sources) that feed the platform's models. Raise the engineering bar and quality: lead and participate in peer technical design reviews, and hold a high standard for testing, observability, evaluation (including for nondeterministic AI outputs), and operational excellence. Communicate clearly with engineers, product partners, and non-technical stakeholders, while developing a deep understanding of the energy domain the platform serves.
