Director, AI Platform Engineering & DevOps

Description

The company is hiring a Director of AI Platform Engineering and DevOps to set the strategy, architecture, engineering and day-to-day operation of its enterprise AI, Kubernetes, GPU and DevOps platforms.

You will work with infrastructure engineering, application development, data science and business stakeholders to build AI and cloud-native platforms that scale, stay secure, control cost and can be run sustainably.

The role drives company-wide use of Private AI, Generative AI, GPU computing, Kubernetes-based platform services, RunAI, automation and DevOps practices.

You will help business and technical teams assess AI use cases, bring workloads onto the platform, improve returns on infrastructure spending and speed up work for developers and data scientists.

Responsibilities

• Set the architecture direction for enterprise AI, Private AI, Generative AI, GPU, Kubernetes and cloud-native platform services.
• Lead the design and growth of scalable GPU infrastructure for AI, machine learning, LLM, data science and high-performance compute workloads.
• Lead Kubernetes platform work, covering workload orchestration, container platform design, resource management, scalability, reliability and operational governance.
• Push DevOps practice forward across platform services: CI/CD, automation, infrastructure as code, configuration management, repeatable deployments and operational efficiency.
• Work with developers, data scientists, application and business architects, enterprise architecture and business leaders to assess AI use cases and pick the right platform solutions.
• Evaluate technologies, vendors, infrastructure designs, GPU configurations, networking, storage and platform tooling against enterprise AI goals.
• Drive adoption of AI platform services through workshops, technical discovery sessions, onboarding, demos and enablement for development and data science teams.
• Support platform users with onboarding, troubleshooting, technical guidance, requirements analysis and day-to-day operations.
• Make sure AI infrastructure is properly designed for applications, availability, migration and business needs, not treated as a box to tick.
• Write technical proposals, business cases, architecture recommendations and cost optimization plans for AI and GPU platform investment.
• Lead capacity planning and the future-state roadmap for platform growth, GPU expansion, workload onboarding and Private AI adoption.
• Work with Enterprise Architecture to keep AI and platform engineering aligned with the wider enterprise technology direction.
• Find ways to raise developer productivity, enable on-prem AI alternatives, cut public cloud AI service costs and support business-led AI initiatives.
• Mentor junior and supporting staff to expand platform support, improve knowledge sharing and reduce reliance on senior architects.
• Make sure platform solutions follow enterprise standards, InfoSec requirements, operational processes and infrastructure best practices.

Requirements

• Extensive experience in enterprise infrastructure architecture, platform engineering, Kubernetes, DevOps, cloud-native technology, AI/ML infrastructure or high-performance computing.
• Several of the following: designing or supporting enterprise Kubernetes or container platforms; running CI/CD, automation and infrastructure as code; architecting GPU infrastructure for AI, machine learning or HPC; working with AI/ML platforms, Generative AI, LLM hosting or Private AI; turning requirements into solutions with developers, data scientists, architects and business stakeholders; running vendor evaluations, technical comparisons and cost-benefit analysis; leading complex cross-functional initiatives from concept through operations.
• Very strong written and verbal communication, including preparing proposals, summaries, roadmaps and executive-level recommendations.
• Strong knowledge of Kubernetes, container orchestration, platform engineering and cloud-native architecture.
• Strong knowledge of DevOps, CI/CD pipelines, GitOps, infrastructure as code, automation and operational process improvement.
• Strong understanding of GPU infrastructure, AI/ML workloads, LLM infrastructure needs and high-performance compute design.
• Ability to weigh complex technical options and recommend scalable, cost-effective, enterprise-ready solutions.
• Ability to explain complex AI, infrastructure and platform topics to business and leadership audiences.
• Strong stakeholder management, with the ability to influence infrastructure, architecture, development, data science and business teams.
• Strong analytical and problem-solving skills focused on performance, scalability, resiliency, cost and operational readiness.
• Ability to run technical discovery sessions, workshops, demos, onboarding and enablement activities.
• Ability to mentor technical staff and drive knowledge transfer across teams.
• Ability to work with limited direction and lead complex initiatives across several teams and priorities.
• Bachelor's degree in computer science, information technology, engineering, data science or a related field is preferred.
• An equivalent mix of education, training, certifications and relevant enterprise technology experience may be considered.
• Preferred: experience with RunAI or similar AI/GPU orchestration platforms.
• Preferred: experience with NVIDIA GPU platforms and AI infrastructure ecosystems.
• Preferred: experience with hybrid cloud, private cloud, virtualization, networking, storage and enterprise compute platforms.
• Preferred: experience supporting AI adoption, developer enablement, workshops, platform onboarding or technical evangelism.
• Preferred: experience preparing executive-level architecture recommendations, investment proposals and technical roadmaps.

Conditions

Base pay ranges from $119,900.00 to $334,200.00 per year. Actual pay depends on qualifications such as knowledge, skills, education and experience, plus location and schedule (full or part-time).

Depending on the role, incentive plans, bonuses or other compensation may be offered.

Benefits

• Health and welfare benefits and other benefits are available.