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Tundra Technical Solutions

Enterprise AI Platform Lead

Toronto, ON, Canada

Pay: $100 to $128 CAD / hour
Job type: Contract
Apply by: Oct 23, 2026
Posting language: English
Posted: Sep 23, 2026

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Original job description

Description

This is a temporary contractor position for an existing vanacny.

Summary

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

AI Platform Strategy & Roadmap

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.

AI Enablement & Innovation

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.

Critical Success Factors

Balances innovation with governance and risk management.
Creates scalable, reusable enterprise AI capabilities.
Delivers measurable business value through AI adoption.
Builds strong partnerships across business and technology teams.
Demonstrates strategic leadership while remaining technically credible.
Drives operational excellence, platform reliability, and responsible AI practices.

Key Performance Indicators (KPIs)

Growth of AI platform adoption across business units.
Number of production AI solutions successfully deployed.
AI platform availability and operational performance.
Reduction in time-to-deploy AI use cases.
Compliance with AI governance and security standards.
User satisfaction and business value delivered through AI initiatives.
Platform cost efficiency and optimization outcomes.

This role operates under a hybrid work model and requires employees to work from the office a minimum of two days per week.

Pay Rate Range

Min Pay Rate: $120

Max Pay Rate: $128

Currency: CAD

Unit: hourly

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More about this job

Responsibilities

Lead the strategy, architecture, engineering, governance, and operations of the enterprise AI platform, enabling secure and scalable adoption of AI, machine learning, and generative and agentic AI. Establish reusable platform capabilities and responsible AI controls, support business adoption, and lead technical teams and stakeholder partnerships while managing budgets and vendors.

Requirements

Requires a bachelor's degree in a relevant technical field, at least eight years of experience in enterprise technology, data, cloud, AI, or platform engineering, and at least three years of leadership experience. Candidates need hands-on enterprise AI and cloud platform experience, including Azure AI Services or equivalent, and expertise in governance, security, enterprise architecture, APIs, and data platforms.

Skills

AI Platform Strategy
Enterprise Architecture
AI Platform Engineering
Machine Learning
Generative AI
Agentic AI
Azure AI Services
OpenAI Technologies
MLOps
DevSecOps
AI Governance
Responsible AI
Cloud Platforms
Data Platforms
Stakeholder Management
Technical Leadership

Visa sponsorship

Not detected in the job text

Keywords

Enterprise AI Platform
Artificial Intelligence
Machine Learning
Generative AI
Agentic AI
Azure AI Services
OpenAI
Snowflake Cortex
Microsoft Copilot
Microsoft Fabric
Azure Data Services
Retrieval-Augmented Generation
Large Language Models
MLOps
DevSecOps
AI Operations
AI Governance
Responsible AI
Model Management
Prompt Management
Vector Search
Model Routing
Observability
Cloud Platforms
Enterprise Architecture
APIs
Data Platforms
Cybersecurity
Privacy
Regulatory Compliance

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