AI Backend Engineer

Company Overview BrightNight is a high-growth renewable power developer and Independent Power Producer (IPP) with a 30-gigawatt portfolio spanning 20 U.S. states. The company develops innovative, dispatchable, and hybrid energy solutions that deliver reliable, cost-efficient renewable power to utilities, data centers, and other high-demand customers across fast-growing energy markets. Supported by strong financial partners, including Goldman Sachs, experienced industry leadership, and proprietary capabilities such as PowerAlpha®, BrightNight is scaling rapidly while differentiating itself through an AI-enabled, automation-driven approach to project development and operations. For candidates, BrightNight offers the opportunity to take on meaningful responsibility, work directly with experienced industry leaders, and grow alongside a company with real momentum and ambitious plans for the future. We’re building a company where intelligence is built in, not bolted on. It is an opportunity to work in a fast-paced, entrepreneurial environment where smart, curious people can make an outsized impact, grow quickly, and help shape the future of reliable clean energy The Opportunity BrightNight is seeking a Senior AI / Backend Engineer to help build the next generation of agentic AI systems that power our proprietary PowerAlpha platform. In this role, you'll design, develop, and productionize AI agents that automate complex engineering, commercial, and operational workflows. You'll work closely with software engineers, AI specialists, and subject matter experts to combine large language models with BrightNight's proprietary optimization models and data, enabling faster decisions, higher-quality outcomes, and greater operational efficiency. This is an opportunity to build production AI—not prototypes—at the intersection of renewable energy, optimization, and modern agentic systems. What You'll Do Design, build, and deploy production-grade AI agents that integrate with BrightNight's proprietary optimization models. Develop scalable backend services supporting agent workflows, APIs, tool execution, memory, persistence, streaming, and observability. Build optimization agents capable of scenario generation, ranking, uncertainty analysis, and decision support. Create robust data ingestion and normalization pipelines that transform complex external data into standardized, validated inputs. Develop comprehensive testing frameworks, including unit, integration, end-to-end, and evaluation harnesses for probabilistic AI systems. Improve agent learning through feedback loops, knowledge capture, validation, and continuous refinement. Partner with engineering, commercial, and operations experts to encode domain expertise into AI skills and knowledge bases. Design safe, reliable human-in-the-loop workflows with appropriate approval checkpoints. Monitor, measure, and continuously improve agent performance, quality, and operational efficiency. What We're Looking For Required Qualifications 5+ years of software engineering experience with a strong focus on backend development. Extensive hands-on experience developing Generative AI applications, including LLM prompting, retrieval, tool/function calling, and agent frameworks (such as Pydantic-AI or similar). Expert-level Python development experience building production APIs, backend services, asynchronous applications, and data access layers. Experience building and deploying agentic workflows involving multi-step reasoning, tool orchestration, memory, state management, and human-in-the-loop processes. Strong software engineering fundamentals, including rigorous unit, integration, and end-to-end testing practices. Experience evaluating and improving non-deterministic AI systems. Practical understanding of where LLMs are most effective—and when deterministic algorithms or optimization models are the better solution. Ability to own complex technical initiatives from architecture through deployment while mentoring other engineers. Preferred Qualifications Experience in renewable energy, utilities, infrastructure, project development, or energy markets. Familiarity with project finance concepts such as IRR, ITC/PTC, LCOE, or EPC cost structures. Experience integrating LLMs with engineering, optimization, financial, or mathematical models. Experience normalizing unstructured data from PDFs, OCR, vendor quotes, or heterogeneous external sources. Experience with PostgreSQL, Google Cloud Platform, Kubernetes, Datadog, MCP servers, and modern AI development tools such as Cursor, Claude Code, or Codex. Experience implementing observability, monitoring, and cost optimization for production AI systems. What Makes You Successful We're looking for someone who: Thinks from first principles and favors pragmatic solutions over unnecessary complexity. Is passionate about building production-ready AI systems—not just experiments. Takes ownership from architecture through deployment and continuous improvement. Enjoys collaborating with cross-functional experts to solve challenging technical problems. Thrives in a fast-paced, entrepreneurial environment where innovation and execution go hand in hand. Balances speed with reliability, always keeping safety, quality, and scalability in mind. Why BrightNight? At BrightNight, you'll have the opportunity to: Build AI systems that solve meaningful, real-world problems in the renewable energy industry. Work on proprietary technology that directly impacts the design and operation of utility-scale energy infrastructure. Collaborate with world-class engineers, AI practitioners, and industry experts. Help shape the future of agentic AI within a rapidly growing clean energy company. Work remotely with a collaborative, high-performing engineering team. Grow your career while helping accelerate the transition to reliable, intelligent clean energy. If you're excited about building production AI systems that combine cutting-edge LLMs with sophisticated optimization and engineering models, we'd love to hear from you.