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

Equinix is the world’s digital infrastructure company, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Job Summary

The Senior Director AI, Chief Revenue Organization leads 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. This role 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
- Build systems 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

Drive Hands-On ML Engineering Excellence

- 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
- Establish best practices for CI/CD, experimentation, model evaluation, and observability across AI systems

Scale Agentic AI Systems

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

Drive Revenue Impact Through AI

- Partner with Sales and go-to-market leadership to embed AI into deal strategy and customer engagements
- Contribute directly to pipeline growth, deal velocity, and account expansion
- Translate AI capabilities into measurable outcomes including conversion improvement, productivity gains, and customer retention

Lead Cross-Functional Execution

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

Build and Lead High-Performing Teams

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

Qualifications

Knowledge and Experience

- 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 finetuning
- Strong experience with retrieval-augmented generation architectures and agentic AI systems
- Proficiency with ML frameworks such as PyTorch or TensorFlow
- Experience with cloud platforms including AWS, GCP, or Azure, and modern data stacks
- Strong understanding of distributed systems, CI/CD, experimentation frameworks, and observability

Skills and Attributes

- Strategic thinker with solid business acumen
- Executive presence and influence
- Structured problem solver
- Systems thinker with enterprise perspective
- Builder of teams and scalable operating models
- Calm, decisive leader in complex environments
- Experience with Salesforce or enterprise CRM ecos

📌 Senior Director AI, Chief Revenue Organization (Toronto)
🏢 Equinix
📍 Toronto