Required Experience

- 7+ years of experience in AI/GEN AI/ML engineering, with solid 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




- Robust 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
- Chance 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

Pay: $90.00-$115.00 per hour

Work Location: Hybrid remote in Toronto, ON (Toronto District)

📌 Senior AI Engineer (Canada)
🏢 Tekstaff IT Solutions
📍 Canada