Note: The job is a remote job and is open to candidates in USA. BrightNight is a high-growth renewable power developer and Independent Power Producer building AI-enabled, automation-driven solutions for reliable clean energy. The company is seeking a Senior AI / Backend Engineer to design, develop, and productionize agentic AI systems for its PowerAlpha platform, integrating large language models with proprietary optimization models and data. The role focuses on scalable backend services, AI agent workflows, data pipelines, testing, observability, and continuous performance improvement.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- Work remotely with a collaborative, high-performing engineering team.
- Grow your career while helping accelerate the transition to reliable, intelligent clean energy.
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