Staff Software Engineer, Energy Intelligence

Palmetto Clean Technology•Charlotte, NC

2d•Hybrid

About The Position

Palmetto is seeking a Staff Software Engineer to join their Energy Intelligence team. This role will focus on building the software and data layer that transforms fragmented energy data into structured intelligence. The engineer will develop services, pipelines, and models for estimating home energy usage, production, and costs, running them as reliable production APIs at scale. The position involves physics-based and machine-learning energy modeling, processing large-scale geospatial and remote-sensing data, handling utility and grid data across US markets, and developing AI systems with LLM-powered agents for data extraction from complex documents. The ideal candidate is a versatile engineer with full-stack capabilities, comfortable with modern AI frameworks and tooling. This role is part of the Data and Energy Intelligence Unit, a multidisciplinary team focused on data-intensive applications in energy modeling, geospatial data, and applied AI. While energy expertise is a plus, strong engineering skills and sound judgment are most valued, with the opportunity to learn the domain on the job.

Requirements

Advanced proficiency in Python for production software, with a demonstrated ability to write clean, maintainable, well-tested code and design solid APIs and services.
Full-stack breadth: comfortable working across backend, modern frontend (e.g., React/TypeScript), and underlying infrastructure.
Hands-on experience building production LLM systems and agents with frameworks like pydantic-ai, LangGraph, or Claude/OpenAI Agent SDKs, including prompting, evals, and extracting structured data from messy, unstructured sources at scale.
Fluency with agentic coding tools, used critically to multiply impact, questioning and pressure-testing their output.
Experience building and operating production systems: APIs and services, data pipelines, relational databases (SQL/PostgreSQL), containerization, cloud platforms (AWS/GCP/Azure), and observability, with sound practices (version control, code review, testing, CI/CD).

Nice To Haves

Geospatial and remote-sensing experience: imagery, elevation/point clouds, and libraries such as rasterio, geopandas, and shapely; PostGIS.
Depth in the modern Python web stack: FastAPI, SQLAlchemy, Pydantic, and async Python.
Frontend depth: React, Vite, TypeScript, and data-fetching/state libraries (e.g., TanStack Query/Router).
Strong quantitative or algorithmic aptitude, and comfort with the Python data stack (pandas, polars, NumPy).
Experience in the clean energy space, with home energy data, or in building electrification and decarbonization.

Responsibilities

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, including LLM- and agent-based systems for extracting structured, validated data from complex, unstructured documents with human-in-the-loop review.
Take models from prototype to production: build APIs, pipelines, and infrastructure for reliable, large-scale operation of physics-based and machine-learning models, ensuring testing and observability.
Work with large geospatial and remote-sensing datasets (imagery, elevation, and related sources) to feed platform models.
Raise the engineering bar and quality by leading and participating in technical design reviews, and upholding high standards for testing, observability, evaluation, and operational excellence.
Communicate clearly with engineers, product partners, and non-technical stakeholders, while developing a deep understanding of the energy domain.