Linux Engineering

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., Deploy and operate vector databases to support retrieval‑augmented generation (RAG) workflows

Partner closely with ML engineers and application teams who will build on top of the platform you create

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

Experience operating platforms across on‑prem, cloud, or hybrid environments

Experience supporting internal platform consumers at scale

Build a foundational GenAI platform from the ground up

Exposure to both on‑prem GPU infrastructure and cloud GenAI workloads

Full‑time

Information Technology

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

Medical insurance

Pension plan

Disability insurance

Child care support