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Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.

Job Summary We are seeking a Director of AI Solutions to lead the design, engineering, and deployment of generative AI and machine learning systems across Sales, Marketing, and Customer Success. This is a hands‑on technical leadership role responsible for building and scaling production‑grade AI systems that directly drive revenue outcomes, including pipeline growth, deal acceleration, customer retention, and operational efficiency. You will operate at the intersection of AI engineering, enterprise architecture, and go‑to‑market strategy, partnering closely with Sales, Product, and Engineering leaders to translate AI capabilities into measurable business value.

Responsibilities

Lead end‑to‑end GenAI and ML system delivery.

Design and deploy generative AI and machine learning solutions embedded in CRM and customer workflows, including LLM‑powered copilots, agentic workflows, retrieval‑augmented generation pipelines, and predictive models.

Own the full lifecycle from data sourcing and model development to evaluation, deployment, and monitoring.

Architect and guide implementation of model training and fine‑tuning pipelines using frameworks such as PyTorch, TensorFlow, and Hugging Face, build real‑time and batch inference systems, embedding pipelines, and vector database integrations, and establish best practices for CI/CD, experimentation, model evaluation, and observability across AI systems.

Design and deploy agent‑based systems capable of multi‑step reasoning, tool usage, and workflow orchestration across enterprise platforms, establishing reusable patterns for prompt management, tool integration, policy enforcement, and agent lifecycle management.

Partner with Sales and go‑to‑market leadership to embed AI into deal strategy and customer engagements, contributing directly to pipeline growth, deal velocity, and account expansion,



and translating AI capabilities into measurable outcomes including conversion improvement, productivity gains, and customer retention.

Collaborate across Engineering, Data, Product, Sales, and Customer Success to deliver integrated AI solutions, translating complex business problems into scalable technical architectures and ensuring alignment across systems, data, and workflows.

Lead and grow teams of ML engineers, ML scientists, and AI architects, establishing a high bar for engineering quality, execution, and technical depth, and building scalable development practices and delivery models for enterprise AI.

Qualifications

12‑15+ years of experience in AI/ML, data science, or distributed systems engineering.

8+ years leading ML or AI engineering teams in platform or infrastructure environments.

Proven track record delivering production‑grade AI systems at enterprise scale.

Experience partnering with Sales, Marketing, or Customer Success organizations to drive business outcomes.

Technical Expertise

Deep hands‑on experience with generative AI, including LLMs, prompt engineering, and fine‑tuning.

Strong experience with retrieval‑augmented generation architectures and agentic AI systems.

Proficiency with ML frameworks such as PyTorch and TensorFlow.

Experience with cloud platforms including AWS, GCP, or Azure and contemporary data stacks.

Strong understanding of distributed systems, CI/CD, experimentation frameworks, and observability.

Leadership and Business Acumen

Ability to operate as both a technical leader and business partner.

Strong executive communication and stakeholder management skills.





Experience influencing senior stakeholders and driving alignment across highly matrixed organizations.

Ability to translate complex technical systems into clear business value.

Experience building AI solutions for Enterprise and driving value through revenue growth such as new logos, recommendations for cross‑sell and upsell.

Preferred Qualifications

Experience with Salesforce or enterprise CRM ecosystems.

Experience building internal AI platforms or developer tooling.

Background in SaaS or enterprise software environments.

Advanced degree in Computer Science, Machine Learning, or a related field.

Pay Range Canada - Toronto Office: 166,000‑248,000 CAD per annum (base pay only). Bonus, equity, and benefits may be offered.

Benefits

Competitive health insurance complementary to provincial coverage.

Retirement savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP), and Tax‑Free Savings Plan (TFSA).

Vacation and paid holidays.

Employee Assistance Program.

Other benefits as per Equinix policy.

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know.

Equinix is an Equal Employment Opportunity and, in the U.S., an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, national origin, ancestry, place of birth, citizenship, sex, pregnancy/childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political/organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

We use artificial intelligence in our hiring process. Learn more here.

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Apply on Kit Job: kitjob.ca/job/2g8t4h

📌 Director, AI Solutions (Toronto)
🏢 Equinix
📍 Toronto