26 Oct
|
Equinix
|
Winnipeg
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.
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 Equinix is building a current generation of AI infrastructure products, and we are looking for senior technical leaders to help shape them. As a Distinguished Engineer on the AI Infrastructure Products team, you will design, build, and launch the platforms and services that let customers run AI inference close to their data, clouds, and partners across Equinix’s global footprint.
This is a hands‑on builder role. You will incubate new products and take them from zero to one, then harden them into reliable platforms that run at global scale. You will work across the stack, from container & service‑based compute platforms and customer‑facing APIs to the networking that connects AI workloads with Equinix Fabric and our broader interconnection portfolio.
As a Distinguished Engineer, you will be the senior‑most technical authority for AI Infrastructure Products, setting the multi‑year architecture vision and shaping how Equinix competes in AI infrastructure. You will operate at a company and industry level, recognized as an expert inside and outside Equinix.
Responsibilities Scope as a Distinguished Engineer
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
Build AI Infrastructure Products
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 fast-moving inference ecosystem (serving frameworks, accelerators, model optimization) and bring the right technologies into our products
Incubate and Launch Zero-to-One Products
Take new ideas from concept to prototype to production launch, partnering closely with Product Management to shape requirements and define MVPs
Move quickly in ambiguous problem spaces: run proofs of concept, make build‑vs‑buy calls, and turn early learnings into a durable architecture??WebPlatform, Scale & Reliability
Architect and run platforms and services that scale across Equinix’s global data center footprint
Apply platform engineering, DevOps, and SRE practices (automation, CI/CD, infrastructure as code, observability, SLOs, incident response) so that what we launch stays reliable at scale
Identify and resolve systemic reliability, performance, and cost issues across the platform
Networking & Interconnection
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
Technical Leadership & Mentorship
Lead architecture and design reviews, and author the 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
Qualifications Technical Expertise
Strong experience building and operating distributed systems and services at scale
Hands‑on production experience with Kubernetes and the cloud‑native ecosystem (containers, operators, Helm, service mesh, or similar)
Proficiency in Go; experience with Python or other systems languages is a plus
Deep experience designing APIs and service‑oriented or microservices architectures
Solid background in platform engineering, DevOps, or SRE, including CI/CD, infrastructure as code (e.g., Terraform), observability, and reliability engineering
Experience with AI/ML inference (e.g., model serving frameworks such as vLLM, Triton, or KServe; GPU scheduling; performance tuning), or a strong, demonstrated interest in growing deep expertise in this space
Working knowledge of networking fundamentals (TCP/IP, routing, BGP, load balancing, overlays) and how they apply to multisite, hybrid, and multi‑cloud environments
Leadership & Experience
Track record of taking new products or platforms from zero to one and through launch
Comfortable operating in ambiguity and driving decisions with incomplete information
Proven ability to influence technical direction across teams without direct authority
Excellent written and verbal communication; able to explain complex technical concepts to technical and non‑technical audiences
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Preferred Qualifications
Experience with GPU infrastructure and accelerated computing (e.g., NVIDIA GPU Operator, CUDA ecosystem, RDMA/RoCE/InfiniBand)
Experience building on or integrating with interconnection or network‑as‑a‑service platformsPay Ranges
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📌 Distinguished Engineer, AI Infrastructure (Winnipeg)
🏢 Equinix
📍 Winnipeg