Senior Director, AI Engineering

Who are we?

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

We are seeking a Senior Director of AI Engineering to lead and scale a high-performing Machine Learning Engineering (MLE) organization. This leader will be responsible for building production-grade AI/ML systems that power next-generation generative and predictive capabilities across the enterprise. The role combines deep technical leadership, organizational scale, and strong business alignment to translate AI innovation into measurable impact.

Reporting to Yang Song within Digital and Innovation Office, this role will work closely with the Data & Engineering team around technology and development. This is a hands-on technical leadership role responsible for building and scaling production-grade AI systems.

This role is critical to transforming AI from experimentation into a scalable, enterprise capability. You will define how AI is built, deployed, and leveraged across the organization—unlocking faster decisions, smarter automation, and sustained competitive advantage.

Responsibilities

Lead and Scale the MLE Organization

• Build, lead, and mentor a global team of Machine Learning Engineers and technical leaders

• Establish a high-performance engineering culture focused on quality, velocity, and accountability

• Drive hiring, onboarding, and career development for MLE talent across regions

Deliver Production-Grade AI/ML Systems

• Own end-to-end delivery of ML platforms, pipelines, and services (training, inference, monitoring)

• Operationalize models into scalable, reliable, and secure production systems

• Partner with Data Science and Product to move from experimentation to deployment

Define AI Engineering Strategy & Architecture

• Set the vision for ML platform architecture, MLOps, and GenAI enablement

• Standardize tools, frameworks, and best practices for model development and deployment

• Ensure systems are built for scale, performance, and cost efficiency

Drive Generative AI and Advanced Analytics

• Lead development of GenAI capabilities (LLMs, RAG, copilots, automation workflows)

• Enable reusable AI services and APIs to accelerate use case delivery

• Stay ahead of industry trends and translate them into enterprise-ready capabilities

Cross-Functional Leadership & Stakeholder Alignment

• Partner with Product, Data, Engineering, and Business leaders to prioritize high-impact use cases

• Communicate strategy, progress, and outcomes to executive stakeholders

• Align AI initiatives with business goals, including revenue growth, efficiency, and customer experience

Governance, Risk, and Responsible AI

• Establish best practices for model governance, monitoring, and lifecycle management

• Ensure compliance with security, privacy, and ethical AI standards

• Implement guardrails for safe and responsible use of AI technologies

Qualifications

• 12–15+ years in software engineering, data engineering, or ML engineering

• 5+ years leading large, distributed engineering teams (including managers of managers)

• Proven track record of delivering ML/AI systems at scale in production environments

• Deep knowledge of machine learning systems, MLOps, and cloud-native architectures

• Experience with ML frameworks (e.g., TensorFlow, PyTorch) and data platforms

• Strong understanding of GenAI/LLMs, prompt engineering, and retrieval-augmented systems

• Familiarity with distributed systems, APIs, and microservices architecture

• Strong ability to translate business strategy into technical execution

• Experience driving large-scale transformation initiatives

• Excellent communication and stakeholder management skills

Preferred:

• Experience building enterprise AI platforms or internal AI products

• Background in both predictive ML and generative AI use cases

• Experience in global delivery models (e.g., US + India engineering hubs)

• Master’s or PhD in Computer Science, Engineering, or related field

• undefined

The targeted pay range for this position in the following location is / locations are:

United States - Redwood City Office GHQ : 298,000 - 446,000 USD / Annual

United States - Dallas Infomart Office DAI : 248,000 - 372,000 USD / Annual

Canada - Toronto Office TRO : 202,000 - 302,000 CAD / Annual

Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location.The pay range shown is based on our compensation structure in place at the time of posting and may be up