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 criteriaFind high-value uses for AI and define how success is measuredDesign, build and ship LLM-powered features and agents from prototype to production, such as automating client data onboardingOwn retrieval and RAG over our data, building on the foundation our data engineers prepareBuild evals and monitoring that track quality, cost and latency, and improve systems based on the resultsHelp refine our customer-facing AI featuresSkills
Must have




Mid-to-senior software engineer who has shipped LLM-based features or agents to production, not only prototypesProduction experience in Python (preferred) or Node.
Js/TypeScriptBuilding with LLMs: prompt and tool design, structured outputs, retrieval/RAG and agent orchestrationEvaluating AI systems: eval sets built from representative data, automated graders, human review and production monitoringAWS 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/CDStrong English and communication skillsNice to have
Agent tool protocols such as MCPSQL and cloud warehouse data (Snowflake preferred)Infrastructure as code (e.
G. Terraform)Exposure to energy, utilities or sustainability data

📌 Applied Ai Engineer (Canada)
🏢 Luxoft
📍 Canada