Kubernetes Platform Engineer

Kubernetes Platform Engineer

This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world. Our culture thrives on finding new and better ways to accelerate what's next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

We are seeking a Kubernetes Platform Engineer (High‑Performance Networking) to lead Kubernetes‑native, RDMA‑class networking for distributed AI inference platforms on HPC clusters. You will own the end‑to‑end technical design that allows Kubernetes‑orchestrated inference workloads (NVIDIA NIMs, vLLM, TensorRT‑LLM) to transparently consume high‑speed fabrics (e.g., HPE Slingshot/CXI) using Operators, DRA, CDI, Multus/secondary CNI, and Kubernetes networking abstractions—without container rebuilds, privileged pods, or manual tuning. This role is central to transforming a traditionally HPC‑centric fabric into a first‑class Kubernetes resource, aligned with modern AI Factory and inference‑as‑a‑service deployment models.

Make HPC fabric capabilities consumable from standard containers

Design the mechanisms to expose RDMA‑capable NIC resources and required runtime components without baking the fabric into images, including mounting/injecting host user‑space libraries (e.g., libcxi + libfabric) in a controlled, supportable way.

Define the reference design and implement for Kubernetes‑native RDMA enablement across:

• Dynamic Resource Allocation (DRA)
• Container Device Interface (CDI)
• Multus + secondary CNIs
• Operator‑driven lifecycle management

Own API and CRD design (ResourceClaims, DeviceClasses, custom CRDs) with long‑term compatibility guarantees.

Make and defend architectural tradeoffs between:

• Device plugins vs DRA
• CDI vs runtime hooks vs admission webhooks
• Shared vs exclusive NIC models
• Performance vs operability vs isolation

Kubernetes Operator Ownership

• Define how distributed inference patterns (KV‑cache movement, prefill/decode separation) map onto Kubernetes primitives.

Ensure out-of-the-box compatibility with:

• NVIDIA NIMs and the NIM Operator
• KServe ServingRuntime / InferenceService
• GPU Operator (CDI mode)
• Publish deployment patterns and validated manifests for inference workloads using RDMA fast paths.

Additional Skills:

Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, Solutions Design, Testing & Automation, User Experience (UX)

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.

– United States of America: Annual Salary USD 111,500 - 211,500 in Colorado // 106,000 - 243,000 in Minnesota & Texas

The listed salary range reflects base salary. Variable incentives may also be offered.

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

No Fees Notice & Recruitment Fraud Disclaimer

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Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.