Senior Principal Technical Product Manager

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.

Position Overview

Equinix is seeking an accomplished Senior Principal Technical Product Manager to lead distributed AI solution development within hybrid and multi-cloud environments. This role is central to incubating AI workload orchestration solutions that leverage Equinix’s global digital infrastructure, delivering secure, scalable, low-latency AI services across cloud, edge, and colocation.

As a key member of Equinix’s Solution Incubation Team, this individual will drive strategy, technical execution, and ecosystem partnerships that enable next-generation AI workloads orchestrated over hybrid multi-cloud fabrics.

Key Responsibilities

Distributed AI Enablement & Hybrid Multi-Cloud Leadership

• Architect and drive distributed AI solutions across hybrid cloud, multi-cloud, edge, and on-prem environments, ensuring seamless workload orchestration, data locality, and optimized AI training/inference pipelines.

• Lead integration and technical enablement with AI hardware providers, cloud platforms, system integrators, and connectivity partners, focusing on multi-cloud networking and interconnection fabric leverage to maximize AI performance.

• Develop reference architectures and scalable blueprints for infrastructure-neutral AI workloads spanning compute, storage, networking, and edge capabilities.

• Drive adoption of standardized APIs, integration patterns, data protection, and security models aligned with hybrid cloud and multi-cloud best practices.

Hybrid Multi-Cloud Networking & Security Stewardship

• Lead the design and implementation of robust hybrid multi-cloud network architectures including VPC/VNet peering, transit gateways, direct interconnections, segmentations, and zero-trust security across AI pipelines.

• Define and enforce cloud-neutral security frameworks encompassing encryption, identity and access management, micro-segmentation, network security monitoring, and compliance focused on distributed AI workloads.

• Collaborate with security, networking, and infrastructure teams to automate security controls, vulnerability management, and incident response for hybrid multi-cloud AI environments.

Product Development & Partner Ecosystem Strategy

• Own end-to-end incubation lifecycle for distributed AI solutions: from concept through POCs and market validation to scalable production deployments in partnership with AI ecosystem players.

• Collaborate with product management, solution architects, engineers, and global partners to translate AI workload requirements into unified solution roadmaps and technical delivery plans.

• Develop technical enablement materials, demos, and documentation to catalyze partner onboarding and customer adoption of hybrid multi-cloud AI architectures.

• Lead technical due diligence and validation of partner solutions for AI distributed training, inference, and data management workflows.

Cross-Functional Leadership & Market Validation

• Act as the central technical liaison bridging AI, networking, security, and operations teams for solution incubation and go-to-market readiness.

• Monitor distributed AI workload performance metrics—latency, throughput, GPU utilization, data transfer efficiency—and drive continuous improvement initiatives.

• Provide subject matter expertise in executive forums influencing product strategy, partnerships, and infrastructure investments for large-scale hybrid AI deployments.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field; advanced degrees (AI/ML, distributed systems, business) preferred.

• 10+ years of technical product management or solutions architecture experience with significant focus on distributed AI…