Senior AI Engineer

This is a temporary contractor position.

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.

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, may require travel between offices up to five (5) days per week. Candidates must be able to accommodate this travel as needed.