Who you are

- 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

- 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 up-to-date data stacks

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

- 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

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

- 15+ years experience

- Bachelor's preferred

What the job involves

- 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

- 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

- 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

- 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

- 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

- 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

- 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

📌 Senior Director of AI (Toronto)
🏢 Equinix
📍 Toronto