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Hydro One

Senior AI Engineer

Toronto, ON, Canada

$90 to $110 CAD / hour · Contract

Apply About employer

Applications open in a new tab.

Job details

Pay: $90 to $110 CAD / hour
Job type: Contract
Apply by: Nov 25, 2026
Experience: 7+ years of experience in AI/GEN AI/ML engineering, with strong expertise in Azure cloud environments
Posting language: English
Posted: Oct 26, 2026

Original job description

Anticipated contract duration: 6-months

Description

This is a temporary contractor position.

At Hydro One, we are scaling our Data & AI Marketplace to deliver enterprise-grade AI solutions that drive measurable business impact.

We are looking for a Senior AI / Generative AI Engineer to design, build, and scale production-grade AI systems and intelligent agents, integrating advanced AI capabilities into enterprise workflows within a secure and governed environment.

What You’ll Bring

Required Experience

7+ years of experience in AI/GEN AI/ML engineering, with strong expertise in Azure cloud environments
Proven track record delivering end-to-end AI solutions in production
Experience with Snowflake or modern enterprise data platforms
Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field

Core AI & Engineering Capabilities

Generative AI & LLMs

Hands-on experience building Generative AI applications (GPT, Claude, Gemini, etc.)
Experience fine-tuning and optimizing LLMs for enterprise use cases
Designing and implementing RAG (Retrieval-Augmented Generation) architectures:
Retrieval & embeddings
Vector search
Grounding & context orchestration

AI Agents & Orchestration

Designing and building AI agents using frameworks such as:
LangChain
Semantic Kernel
Azure OpenAI Service
Azure Open AI

Experience with:

Multi-agent systems
Tool/function calling
Workflow automation and orchestration

Azure AI & Platform Engineering

Strong experience across the Azure AI ecosystem:
Azure OpenAI
Azure AI Search
Azure AI Foundry
Azure Machine Learning
Azure Fabric
Snowflake
Integration with enterprise services:
Azure Cognitive Services
Azure Data Lake
Azure Event Hub
Experience deploying scalable solutions on:
Azure Kubernetes Service (AKS)
Distributed, cloud-native architectures

Software Engineering

Strong programming skills in Python
Experience building APIs (FastAPI or similar)
Experience with microservices architecture and enterprise system integration
Familiarity with containerization (Docker/Kubernetes)

MLOps, LLMOps & Governance

Experience implementing MLOps / LLMOps practices:
Azure DevOps, MLflow, CI/CD pipelines
Model evaluation frameworks
Monitoring, observability, performance tracking
Strong understanding of Responsible AI practices:
Security & data protection
Risk management & guardrails
Compliance with enterprise governance standards

What You’ll Work On

Build enterprise-grade AI agents leveraging internal data and workflows
Develop AI-powered search, discovery, and insight-generation platforms
Design scalable GenAI decision-support systems for business and executive users
Implement secure, governed AI solutions in a regulated enterprise environment
Operationalize AI solutions that deliver real, measurable business value

Who You Are

A very hands-on expert who can take solutions from concept → production → scale
Comfortable working in fast-evolving and ambiguous AI environments
Passionate about building secure, reliable, and responsible AI systems
Strong collaborator who thrives in cross-functional teams
Motivated to solve complex business problems using advanced AI

Preferred Skills

Experience with Azure Foundry-based RAG systems
Familiarity with NLP / text analytics applications
Experience contributing to open-source AI projects or research
Experience with GitHub-based development workflows
Exposure to enterprise-scale AI deployments and governance frameworks

Contract Details

Contract role with hybrid model (approx. 2 days onsite) it can be asked for more depends on company policy
Opportunity to work on cutting-edge AI initiatives within Hydro One’s Data & AI Marketplace Delivery team

Why Join Us?

Work on enterprise-scale AI transformation initiatives
Shape how AI is adopted across a regulated, high-impact organization
Build secure, governed, production AI systems - not just prototypes
Collaborate with a team focused on innovation, quality, and real business value

This is a hybrid position requiring the successful candidate to work on-site in Toronto a minimum of two (2) days per week. Occasional travel to the Markham and/or Barrie offices will be required based on project needs. In support of business and project requirements, Hydro One may require travel between offices up to five (5) days per week. Candidates must be able to accommodate this travel as needed.

Pay Rate Range

Min Pay Rate: $90

Max Pay Rate: $110

Currency: CAD

Unit: hourly

Apply About employer

More about this job

Responsibilities

Build and scale production-grade AI agents, search and discovery platforms, and decision-support systems that integrate internal data and enterprise workflows. Deliver secure, governed, and scalable AI solutions, and operationalize them to produce measurable business value.

Requirements

Requires 7+ years of AI, generative AI, or machine learning engineering experience, strong Azure expertise, and a track record delivering end-to-end production AI solutions. Also requires Python and enterprise AI engineering capabilities, with experience in areas such as LLMs, RAG, AI agents, data platforms, MLOps/LLMOps, and responsible AI; a bachelor's or master's degree in a related field is specified.

Skills

Generative AI
Large Language Models
Azure
Python
Retrieval-Augmented Generation
AI Agents
LangChain
Semantic Kernel
Azure OpenAI
Azure AI Search
Snowflake
FastAPI
Microservices
MLOps
LLMOps
Responsible AI

Visa sponsorship

Not detected in the job text

Keywords

Generative AI
Large Language Models
Azure
Azure OpenAI
Azure AI Search
Azure AI Foundry
Azure Machine Learning
Azure Fabric
Snowflake
Python
FastAPI
Retrieval-Augmented Generation
Vector Search
Embeddings
LangChain
Semantic Kernel
AI Agents
Multi-Agent Systems
Tool Calling
Workflow Automation
Azure Kubernetes Service
Docker
Microservices
MLOps
LLMOps
MLflow
Azure DevOps
CI/CD
Responsible AI
Enterprise Data Governance

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