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

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

Skills and Attributes

Strategic thinker with strong 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 ecosystems

Experience building internal AI platforms or developer tooling

Background in SaaS or enterprise software environments

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