Senior Energy AI Engineer: LLMs for Ops

Luxoft; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Luxoft seeks an applied AI engineer to advance AI across our energy solutions platform. The role focuses on building production-grade LLM-powered features and agents, from data onboarding to deployment, with emphasis on retrieval, RAG, and monitoring.

You will collaborate closely with product teams to define success metrics and deliver measurable AI improvements. The ideal candidate has hands-on production experience with Python or Node.js/TypeScript, strong communication skills, and a track

Qualifications

• Shipped LLM-based features or agents to production.
• Experience building with Python (preferred) or Node.js/TypeScript.
• Proficient in prompt design, tool design, and structured outputs for LLMs.
• Experience with retrieval and RAG workflows.
• Proficient in evaluating AI systems with automated and human-in-the-loop methods.
• Experience with AWS or other enterprise cloud platforms (AWS Bedrock preferred).
• Daily use of AI coding tools and scaling AI workflows, including CI/CD.

Responsibilities

• Collaborate with product teams to define and execute technical criteria.
• Identify high-value AI use cases and define success metrics.
• Design, build, and ship LLM-powered features and agents from prototype to production.
• Own retrieval and RAG over data and leverage data prepared by engineers.
• Build evals and monitoring for quality, cost and latency and improve systems.
• Help refine customer-facing AI features.

Skills

LLM deployment

Python production

Node.js/TypeScript

Prompt and tool design

Retrieval/RAG

Evaluation & monitoring

CI/CD

Cloud platforms (AWS Bedrock)

English communication

Agent orchestration

Tools

Terraform

MCPSQL

Snowflake

Job description

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 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 features

SKILLS

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 skills

Nice 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