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Luxoft

Applied AI Engineer

Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 29, 2026

Original 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 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

Mandatory Skills Description:

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 Skills Description:

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

Languages:

English: B2 Upper Intermediate

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More about this job

Responsibilities

Identify valuable AI use cases, define success measures, and build and ship production LLM features and agents, including automated client data onboarding. Own retrieval and RAG over prepared data, develop evaluation and monitoring systems for quality, cost, and latency, and collaborate with product teams to improve customer-facing AI features.

Requirements

Requires mid-to-senior software engineering experience, including production delivery of LLM-based features or agents and production experience with Python or Node.js/TypeScript. Candidates should have experience with LLM design, retrieval and RAG, agent orchestration, AI evaluation and monitoring, enterprise cloud AI services, and AI-native development workflows; strong English communication is also required.

Skills

Python
Node.js
TypeScript
Large Language Models
Prompt Design
Tool Design
Structured Outputs
Retrieval-Augmented Generation
Agent Orchestration
AI Evaluation
Production Monitoring
AWS
AWS Bedrock
PostgreSQL
Snowflake
CI/CD

Visa sponsorship

Not detected in the job text

Keywords

Applied AI
Large Language Models
AI Agents
Python
Node.js
TypeScript
Ruby On Rails
PostgreSQL
Snowflake
AWS
AWS Bedrock
Prompt Design
Tool Design
Structured Outputs
Retrieval-Augmented Generation
Agent Orchestration
AI Evaluation
Automated Graders
Human Review
Production Monitoring
CI/CD
Model Quality
Latency
Cost Optimization
MCP
SQL
Terraform
Energy
Renewable Energy
Data Onboarding

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