Platform Engineer

Kerry Search Partners provided pay range

This range is provided by Kerry Search Partners. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

We are a global leader in the semiconductor manufacturing ecosystem, driving the technology behind virtually every electronic device in the world. Our innovations power the production of laptops, smartphones, VR devices, smart cars, and more. At the forefront of technological advancement, we invest heavily in research and development, fostering an environment where innovation thrives. Our teams of engineers, data scientists, and problem-solvers tackle the toughest challenges, ensuring no two days are the same.

The Information Technology team plays a critical role in supporting the organization’s global operations. IT connects people, processes, and technology to enhance business growth and employee productivity. By focusing on user empowerment and process excellence, IT helps unlock the full potential of advanced technology to drive operational success.

We are building a core Generative AI platform to enable internal engineering, IT, and business teams to rapidly prototype and deploy GenAI applications. This role is not application development
—it is about designing, building, and operating the foundational AI platform that others will consume.

The platform will support both on‑premises GPU infrastructure and cloud environments
, with Kubernetes at its core. You’ll work on everything from GPU provisioning and LLM deployment to vector databases, security, and reliability—owning the platform end to end.

• Build and operate a GenAI platform that supports internal products such as AI assistants and engineering tooling
• Design and maintain Kubernetes‑based AI infrastructure running on on‑prem GPU clusters and cloud environments
• Configure and manage LLMs (e.g., open‑source models such as LLaMA variants) for enterprise use
• Deploy and operate vector databases to support retrieval‑augmented generation (RAG) workflows
• Ensure high availability, scalability, and efficient GPU utilization across expensive compute environments
• Partner closely with ML engineers and application teams who will build on top of the platform you create
• Implement secure, compliant, and observable infrastructure suitable for enterprise adoption
• Leverage Linux and open‑source tooling to optimize performance in high‑performance computing (HPC) environments

• Strong Linux systems background (on‑prem experience is essential)
• Deep experience with Kubernetes as a core platform (deploying, operating, troubleshooting)
• Hands‑on experience building or operating AI/ML platforms (not just consuming them)
• Experience configuring and managing GPU infrastructure for AI/ML workloads
• Familiarity with LLMs, GenAI infrastructure, and vector databases
• Exposure to HPC environments and high‑throughput workloads
• Experience operating platforms across on‑prem, cloud, or hybrid environments

• Understanding of cost optimization and scheduling for GPU‑heavy workloads
• Experience supporting internal platform consumers at scale

• Build a foundational GenAI platform from the ground up
• Work on real, production GenAI systems
  , not demos or experiments
• High ownership, high impact, and deep technical challenges
• Exposure to both on‑prem GPU infrastructure and cloud GenAI workloads

Mid‑Senior level

Full‑time

Information Technology

Semiconductor Manufacturing, Manufacturing, and Appliances, Electrical, and Electronics Manufacturing

• Medical insurance
• Pension plan
• Paid paternity leave
• Tuition assistance
• Disability insurance
• Child care support
• Vision insurance
• Paid maternity leave
• Student loan assistance
• 401(k)