Equinix is seeking to lead distributed AI solution development within hybrid and multi-cloud environments, incubating AI workload orchestration solutions that leverage Equinix’s global digital infrastructure.
Requirements
- 10+ years of technical product management or solutions architecture experience with significant focus on distributed AI workloads, hybrid multi-cloud networking, and infrastructure security.
- Proven ability designing and managing hybrid/multi-cloud network fabrics, interconnections (private and public), and zero-trust security models for enterprise cloud solutions.
- Hands-on experience with AI/ML infrastructure components: GPUs, high-performance compute, distributed storage, Kubernetes, MLOps, and hybrid cloud orchestration.
- Deep understanding of cloud provider networking – AWS, Azure, GCP – and cloud interconnection services supporting distributed applications.
- Experience with Equinix’s Fabric, Network Edge, and interconnection platforms or equivalent hybrid/multi-cloud infrastructure services.
- Background in large-scale AI/ML platform deployment, edge AI, and hybrid multi-cloud solution incubation.
- Familiarity with AI governance, model security frameworks, and privacy requirements in multi-jurisdiction hybrid cloud environments.
Responsibilities
- 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.
- 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.
Other
- Bachelor’s degree in Computer Science, Engineering, or related field; advanced degrees (AI/ML, distributed systems, business) preferred.
- Strong collaborator and communicator able to lead cross-organizational initiatives across product, engineering, security, and partner ecosystems globally.
- Experience building and enabling complex AI partner ecosystems including hardware providers, cloud platforms, system integrators, and telecom/connectivity vendors.
- This position reports to the VP, Partner Ecosystem Solution Development and works closely with engineering leadership, solution architects, and AI partnership teams to drive technical innovation and market validation in AI infrastructure solutions.
