AI Platform Lead

Hydro One; Toronto; On-site; CAD 140,000 - 210,000; Full time

Job summary

Hydro One seeks an AI Platform Lead to shape the strategy and governance of the enterprise AI platform. You will drive architecture, tooling, and services for AI, ML, generative AI, and agentic AI across the organization.

You will partner with security, privacy, data teams, and business leaders to scale AI responsibly while delivering measurable business value and ensuring reliability, compliance, and governance across platforms.

Qualifications

• Bachelor's degree in a relevant field and 8+ years in enterprise technology or platform engineering.
• Proven leadership experience managing technical teams or enterprise platforms.
• Hands-on experience with enterprise AI, ML, and cloud platforms.
• Strong governance, security, and operational controls experience.

Responsibilities

• Define and execute the enterprise AI platform strategy aligned with business objectives.
• Develop a multi-year roadmap for AI platform capabilities, tooling, and services.
• Evaluate emerging AI technologies for enterprise adoption opportunities.
• Establish standards and reference architectures for AI, ML, Generative AI, and Agentic AI solutions.
• Lead design, development, deployment, and operation of enterprise AI platforms and services.
• Ensure platform reliability, scalability, performance, and cost optimization.
• Implement DevSecOps, MLOps, and AI Ops across the AI lifecycle.
• Oversee production support, incident management, and monitoring.

Skills

Bachelor's degree

8+ years experience

Leadership 3+ yrs

Enterprise AI

Azure AI Services

OpenAI technologies

Platform governance

Enterprise architecture

Communication skills

Education

Bachelor's degree in Computer Science, Engineering, Data Science, IT, or related field

Tools

Cloud platforms (Azure)

Job description

The AI Platform Lead is responsible for the strategy, architecture, governance, engineering, and operational management of the enterprise AI platform. This role enables the safe, scalable, and responsible adoption of Artificial Intelligence, Machine Learning, Generative AI, and Agentic AI capabilities across the organization.

The AI Platform Lead will establish and evolve the foundational AI platform, including model management, AI engineering services, governance controls, integration patterns, observability, and operational processes. The role partners closely with business leaders, data teams, security, privacy, architecture, and technology delivery teams to accelerate AI adoption while ensuring reliability, compliance, and measurable business value.

Key Responsibilities

• Define and execute the enterprise AI platform strategy aligned with business objectives.
• Develop and maintain a multi-year roadmap for AI platform capabilities, tooling, and services.
• Evaluate emerging AI technologies and determine enterprise adoption opportunities.
• Establish standards and reference architectures for AI, ML, Generative AI, and Agentic AI solutions.

Platform Engineering & Operations

• Lead the design, development, deployment, and operation of enterprise AI platforms and services.
• Establish reusable platform services for model deployment, prompt management, vector search, model routing, monitoring, and evaluation.
• Ensure platform reliability, scalability, performance, and cost optimization.
• Implement DevSecOps, MLOps, and AI Ops practices across the AI lifecycle.
• Oversee production support, incident management, monitoring, and operational readiness processes.

Governance, Security & Responsible AI

• Establish AI governance frameworks, controls, and review processes.
• Ensure compliance with privacy, cybersecurity, data protection, and regulatory requirements.
• Define and enforce responsible AI standards, guardrails, testing methodologies, and approval workflows.
• Implement auditability, monitoring, logging, model performance tracking, and risk management capabilities.
• Partner with Legal, Compliance, Risk, and Cyber Security teams to ensure enterprise readiness.
• Enable business units to adopt AI through governed self-service capabilities.
• Support development of AI assistants, copilots, predictive models, and intelligent automation solutions.
• Drive adoption of approved enterprise AI tools and platforms.
• Create reusable AI patterns, templates, accelerators, and best practices.
• Promote innovation while balancing governance and operational risk.

Data & Integration Alignment

• Partner with enterprise data platform teams to ensure high-quality, governed data access for AI workloads.
• Collaborate with integration teams to expose enterprise data and services through secure APIs and approved interfaces.
• Ensure AI solutions integrate effectively with business applications and enterprise workflows.

Leadership & Stakeholder Management

• Lead and mentor AI engineers, platform engineers, data scientists, and technical specialists.
• Build relationships with technology leaders, business stakeholders, and external vendors.
• Manage platform budgets, vendor relationships, licensing, and contracts.
• Present AI platform strategy, risks, and outcomes to executive leadership.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, or related field.
• 8+ years of experience in enterprise technology, data, cloud, AI, or platform engineering roles.
• 3+ years of leadership experience managing technical teams or enterprise platforms.
• Hands-on experience with enterprise AI, machine learning, and cloud platforms.
• Strong experience with Azure AI Services, OpenAI technologies, machine learning platforms, or equivalent enterprise AI ecosystems.
• Experience implementing platform governance, security, and operational controls.
• Strong understanding of enterprise architecture, APIs, cloud services, and data platforms.
• Excellent communication, stakeholder management, and leadership skills.

Preferred Qualifications

• Experience with Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), and LLM platforms (Snowflake Cortex and Microsoft Copilot)
• Experience with MLOps frameworks and AI lifecycle management.
• Knowledge of Snowflake, Microsoft Fabric, Azure Data Services, or similar platforms.
• Cloud certifications (Azure, Snowflake, ServiceNow, etc.).
• Experience in regulated industries with strong governance and compliance requirements.