Director, AI Platform Engineering & DevOps

Wayne, United States of America | Full time | Hybrid | R1563456 The Director, AI Platform Engineering & DevOps will be responsible for leading the strategy, architecture, engineering, and operational enablement of enterprise AI, Kubernetes, GPU, and DevOps platforms. This role partners with infrastructure engineering, application development, data science teams, and business stakeholders to design scalable, secure, cost-effective, and operationally sustainable AI and cloud-native platforms.

The role supports enterprise adoption of Private AI, Generative AI, GPU-based computing, Kubernetes-based platform services, RunAI capabilities, automation, and DevOps practices. The position is accountable for helping business and technical teams evaluate AI use cases, onboard workloads, optimize infrastructure investments, and accelerate developer and data science productivity.

Essential Functions

Define and drive architecture strategy for enterprise AI, Private AI, Generative AI, GPU, Kubernetes, and cloud-native platform services. Lead design and evolution of scalable GPU infrastructure to support AI, machine learning, LLM, data science, and high-performance compute workloads. Provide Kubernetes platform leadership, including workload orchestration, containerized platform design, resource management, scalability, reliability, and operational governance. Advance DevOps practices across platform services, including CI/CD enablement, automation, infrastructure as code, configuration management, deployment repeatability, and operational efficiency. Partner with developers, data scientists, application architects, business architects, enterprise architecture, and business leaders to assess AI use cases and determine appropriate platform solutions. Evaluate technology options, vendor capabilities, infrastructure designs, GPU configurations, networking, storage, and platform tooling to support enterprise AI objectives. Drive adoption of