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Sr. Director, AI Infrastructure

Job in Seattle, King County, Washington, 98127, USA
Listing for: Coupang
Full Time position
Listed on 2026-07-17
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations, AI Engineer (Applied/Software), IT Project Manager, SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 184000 - 376000 USD Yearly USD 184000.00 376000.00 YEAR
Job Description & How to Apply Below

Sr. Director Back-end Engineering – AI Infrastructure Orchestration Role Overview

  • Define and execute the long‑term vision and roadmap for the company’s AI infrastructure orchestration layer, aligning it with overall business and AI Services goals.
  • Lead, mentor, and grow a high‑performing engineering and operations team focused on AI infrastructure and platform engineering.
  • Manage budget and resource allocation for AI infrastructure deliverables.
  • Act as a key liaison between AI Infra and other services owners, core engineering, Cloud infrastructure, and executive leadership.
AI Infra Development and Operations
  • Oversee the design, implementation, and maintenance of the core orchestration platforms for large‑scale AI model training (e.g., distributed training, hyperparameter tuning) and deployment (e.g., containerization, serverless functions, edge deployment).
  • Ensure reliability, security, and compliance of the AI infrastructure, meeting strict standards for data governance and model integrity.
  • Establish Service Level Objectives (SLOs) and Key Performance Indicators (KPIs) for the AI platform services and lead efforts for continuous optimization and performance tuning.
Success Metrics

A successful Senior Director - AI Infrastructure Orchestration will be measured by:

  • The time‑to‑market for AI infrastructure build, scale and operate.
  • The resource utilization rate and cost efficiency of the AI compute infrastructure.
  • The reliability and uptime of the core AI platform services.
  • The talent retention and development within the AI Infrastructure team.
Technology and Architecture
  • Select, evaluate, and integrate the core technologies required for the AI stack (e.g., Kubernetes, Kubeflow, Ray, ML frameworks, GPU/accelerator management, distributed file systems).
  • Champion infrastructure‑as‑code (IaC) principles to manage and provision AI resources consistently and at scale.
Basic Qualifications
  • Education:

    Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • Experience:

    15+ years of progressive experience in software engineering, infrastructure, or platform operations.
  • 5+ years of experience leading and managing technical teams, ideally in a Director or Sr. Director level.
  • Deep, hands‑on experience designing and operating large‑scale distributed systems and cloud‑native architectures
    .
  • Proven experience specifically with AI infrastructure orchestration (e.g., using Kubernetes, Kubeflow, or similar MLOps tools) and managing accelerated compute resources (GPUs, TPUs, etc.).
  • 15+ years of Cloud backend engineering, Cloud Design, Deployment, Dev Ops.
  • 15+ years of experience leading system design, architecture leveraging private clouds and AWS and/or Azure/GCP.
  • 10+ years of demonstrable building and operating infrastructure as code. Infra automation, comfortable with many flavors of Linux.
  • 15+ years of experience in building high‑performance, highly‑available and scalable distributed systems in the cloud.
  • 15+ years of experience in building and managing high‑performance, highly‑available and scalable hybrid cloud environments.
  • Excellent cross‑group collaboration, outstanding verbal and written communication.
Skills
  • Expert‑level knowledge of containerization and orchestration (Docker, Kubernetes).
  • Strong background in Dev Ops and MLOps principles and tooling.
  • Proficiency in at least one modern programming language (e.g., Python, Go).
  • Exceptional strategic planning, organizational, and written/verbal communication skills.
Preferred Qualifications
  • Prior experience managing infrastructure for training and inference of large language models (LLMs) or foundation models.
  • Experience in a regulated industry with strict compliance requirements.
  • AI private cloud - building and operating.
Pay & Benefits

Our compensation reflects the cost of labor across several US geographic markets. Base pay ranges from $184,000/year in our lowest geographic market to $376,000/year in our highest geographic market. Pay is based on market location and may vary depending on job‑related knowledge, skills, and experience.

General Description of All Benefits
  • Medical/Dental/Vision/Life, AD&D insurance
  • Flexible Spending Accounts (FSA) & Health…
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