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Equinix

Global data center, colocation, interconnection provider

Distinguished Engineer - AI Infrastructure

Platform EngineeringUpdated on Nov 11
Full-timeHybrid

About the Job

Requirements

  • Strong experience building and operating distributed systems and services at scale.
  • Hands-on production experience with Kubernetes and the cloud-native ecosystem, including containers, operators, Helm, service mesh, or similar technologies.
  • Proficiency in Go; experience with Python or other systems languages is a plus.
  • Deep experience designing APIs and service-oriented or microservices architectures.
  • A solid background in platform engineering, DevOps, or site reliability engineering, including continuous integration and continuous delivery, infrastructure as code such as Terraform, observability, and reliability engineering.
  • Experience with AI/ML inference, such as model-serving frameworks including vLLM, Triton, or KServe; GPU scheduling; performance tuning, or a strong demonstrated interest in developing deep expertise in this space.
  • Working knowledge of networking fundamentals, including TCP/IP, routing, BGP, load balancing, and overlays, and how they apply to multisite, hybrid, and multi-cloud environments.
  • A track record of taking new products or platforms from zero to one and through launch.
  • Ability to operate in ambiguity and drive decisions with incomplete information.
  • Proven ability to influence technical direction across teams without direct authority.
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Responsibilities

  • Define and own the multi-year technical vision and reference architecture for AI infrastructure across Equinix, aligning product, platform, and network strategy.
  • Influence executive leadership and company-wide technology investments, and represent Equinix with strategic customers, partners, standards bodies, and industry forums.
  • Mentor and develop Senior Principal and Principal Engineers, and shape the technical talent bar for the organization.
  • Design, build, and operate infrastructure and inference-related products and services, and the APIs customers use to consume them.
  • Write production-quality code, primarily in Go, and set a high bar for code quality, testing, and design reviews.
  • Design API-first, service-oriented architectures that are secure, well documented, and easy for customers and partners to integrate with.
  • Track the inference ecosystem, including serving frameworks, accelerators, and model optimization, and bring appropriate technologies into products.
  • Take new ideas from concept to prototype to production launch, partnering closely with Product Management to shape requirements and define minimum viable products.
  • Run proofs of concept, make build-versus-buy decisions, and turn early learnings into durable architecture in ambiguous problem spaces.
  • Shape the product roadmap by translating customer needs and market shifts into technical strategy.
  • Architect and run platforms and services that scale across Equinix’s global data center footprint.
  • Apply platform engineering, DevOps, and site reliability engineering practices, including automation, continuous integration and continuous delivery, infrastructure as code, observability, service-level objectives, and incident response, to maintain reliability at scale.
  • Identify and resolve systemic reliability, performance, and cost issues across the platform.
  • Integrate AI infrastructure products with Equinix Fabric, Network Edge, and other interconnection products so customers can securely connect AI workloads to clouds, partners, and their own environments.
  • Partner with network architecture and product teams to design low-latency, resilient connectivity for distributed inference.
  • Lead architecture and design reviews, and author design documents and decision records that guide the team.
  • Mentor and grow engineers, raise the technical bar, and help build a strong engineering culture on a new team.
  • Collaborate with Product, Engineering, Security, Operations, and go-to-market teams, and engage directly with strategic customers and partners.

Desired Qualifications

  • Experience with GPU infrastructure and accelerated computing, such as NVIDIA GPU Operator, CUDA ecosystem, RDMA/RoCE, or InfiniBand.
  • Experience building on or integrating with interconnection or network-as-a-service platforms.
  • Background at a cloud provider, data center, or infrastructure-as-a-service company.
  • Open-source contributions, such as CNCF projects, conference talks, or published technical writing.

About the Company

Equinix

Global data center, colocation, interconnection provider

Equinix provides data center space, colocation, and interconnection services to businesses worldwide. Customers rent space to house servers and use interconnected networks inside Equinix data centers, enabling low-latency data transfer between networks and cloud providers. Unlike competitors that focus only on space, Equinix combines a global footprint with a large ecosystem of over 10,000 customers for direct, high-speed connections. Its goal is to enable fast, reliable digital operations and support customers’ digital transformation and multi-cloud strategies.

Company size
10,001+
Company stage
IPO
Headquarters
Redwood City, CA
Founded
1998

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