Project description
Our client is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and Python services, PostgreSQL, Snowflake and AWS. We're looking for an applied AI engineer to build AI with real, measurable benefit across our operations and products.
Responsibilities
- Work closely with product teams to help define and execute technical criteria
- Find high-value uses for AI and define how success is measured
- Design, build and ship LLM-powered features and agents from prototype to production, such as automating client data onboarding
- Own retrieval and RAG over our data, building on the foundation our data engineers prepare
- Build evals and monitoring that track quality, cost and latency, and improve systems based on the results
- Help refine our customer-facing AI features
Skills
Must have
- Mid-to-senior software engineer who has shipped LLM-based features or agents to production, not only prototypes
- Production experience in Python (preferred) or Node.js/TypeScript
- Building with LLMs: prompt and tool design, structured outputs, retrieval/RAG and agent orchestration
- Evaluating AI systems: eval sets built from representative data, automated graders, human review and production monitoring
- AWS or another enterprise cloud platform, including its AI services (AWS Bedrock preferred)
- AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows across a team and into the development lifecycle, including CI/CD
- Strong English and communication skills
Nice to have
- Agent tool protocols such as MCP
- SQL and cloud warehouse data (Snowflake preferred)
- Infrastructure as code (e.g. Terraform)
- Exposure to energy, utilities or sustainability data
