Distinguished Engineer, AI Infrastructure

Equinix

. Define and own the multi-year technical vision and reference architecture for AI infrastructure across Equinix .

Posted 10/16/2026full-timeUnited StatesMid-LevelSenior💰 $230,000 - $414,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and operating AI infrastructure, with a strong focus on distributed systems, API development, and platform engineering. Proven ability to influence technical direction and collaborate across teams while driving innovative solutions from concept to production.

Highest-signal resume keywords

Distributed Systems EngineeringAPI DevelopmentKubernetes ProficiencyPlatform EngineeringDevOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Go ProgrammingPython ProgrammingAPI DesignMicroservices ArchitectureCI/CD ImplementationInfrastructure as CodeObservability EngineeringAI/ML InferenceTCP/IP KnowledgeLoad Balancing

Soft Skills

Influencing Technical DirectionExcellent Communication SkillsMentoring EngineersOperating in AmbiguityCollaboration

Tools & Technologies

KubernetesCloud-Native EcosystemEquinix FabricNetwork EdgeMulti-Cloud EnvironmentsSRE PracticesAutomation ToolsIncident Response ToolsObservability ToolsGPU Infrastructure

Industry Keywords

AI InfrastructureData Center OperationsInterconnection ProductsNetwork-as-a-ServiceHybrid EnvironmentsOpen-Source ContributionsTechnical WritingConference TalksInfrastructure-as-a-ServiceBGP Knowledge

Tech Stack

Tools & technologies

CloudDistributed SystemsKubernetesMicroservicesPythonTCP/IPGo

About the role

Key responsibilities & impact

Define and own the multi-year technical vision and reference architecture for AI infrastructure across Equinix
Influence executive leadership and company-wide technology investments
Represent Equinix with strategic customers, partners, standards bodies, and industry forums
Mentor and develop Senior Principal and Principal Engineers
Design, build, and operate infrastructure and inference-related products and services
Develop customer-facing APIs for consuming AI infrastructure products
Write production-quality code primarily in Go
Design secure, documented, API-first, service-oriented architectures
Track inference technologies and integrate suitable technologies into products
Take new ideas from concept through prototype to production launch
Run proofs of concept and make build-versus-buy decisions
Translate customer needs and market shifts into technical strategy
Architect and operate platforms across Equinix’s global data center footprint
Apply platform engineering, DevOps, and SRE practices including automation, CI/CD, infrastructure as code, observability, SLOs, and incident response
Identify and resolve systemic reliability, performance, and cost issues
Integrate AI infrastructure with Equinix Fabric, Network Edge, and other interconnection products
Design low-latency, resilient connectivity for distributed inference
Lead architecture and design reviews and author design documents and decision records
Collaborate with Product, Engineering, Security, Operations, and go-to-market teams
Engage directly with strategic customers and partners

Requirements

What you’ll need

Strong experience building and operating distributed systems and services at scale
Hands-on production experience with Kubernetes and the cloud-native ecosystem
Proficiency in Go
Experience with Python or other systems languages is a plus
Deep experience designing APIs and service-oriented or microservices architectures
Background in platform engineering, DevOps, or SRE
Experience with CI/CD, infrastructure as code, observability, and reliability engineering
Experience with AI/ML inference or strong demonstrated interest in developing expertise in this area
Working knowledge of TCP/IP, routing, BGP, load balancing, and overlays
Experience with multisite, hybrid, and multi-cloud environments
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
Excellent written and verbal communication skills
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Preferred: GPU infrastructure and accelerated computing experience
Preferred: interconnection or network-as-a-service platform experience
Preferred: cloud provider, data center, or infrastructure-as-a-service company background
Preferred: open-source contributions, conference talks, or published technical writing

Benefits

Comp & perks

Employee Assistance Program available to all employees
US health, life, disability, and voluntary insurance plans
US retirement plan contributions
US paid time off and paid holidays
Canada healthcare coverage, life, disability, and optional benefit plans
Canada Defined Contribution Pension Plan (DCPP)
Canada Group Retirement Savings Plan (RRSP)
Canada Tax-Free Savings Plan (TFSA)
Canada vacation, personal time, and paid holidays
Bonus eligibility
Potential equity offering depending on the position
Disability accommodations during the employment process