Kubernetes (K8S) / HPC Engineer

Capgemini; Atlanta (GA); Remote; USD 77,000 - 151,000; Full time

Benefits offered by this job

Paid time off and holidays

Medical, dental, and vision coverage

Retirement savings plans (e.g., 401(k)

Life and disability insurance

Employee assistance programs

Job summary

Capgemini Engineering seeks an experienced Kubernetes/HPC Engineer to design, deploy, and support scalable compute platforms for AI/ML, simulation, and HPC workloads, spanning cloud and on-prem environments. You will lead container orchestration, GPU provisioning, and automation efforts to improve reliability and performance.

With 5+ years in Kubernetes/Platform Engineering, you will optimize HPC clusters, implement CI/CD, and drive observability across distributed systems, leveraging AKS, GKE,

Qualifications

• 5+ years of Kubernetes, Platform Engineering, Cloud Infrastructure, DevOps, SRE or related disciplines.
• 2+ years supporting HPC environments or large-scale compute clusters.
• Hands-on with Kubernetes, Docker, Helm, container orchestration.
• Experience managing HPC clusters and schedulers like Slurm/Volcano.
• Expertise with NVIDIA GPU infrastructure for ML and accelerated computing.
• Strong Linux administration, automation, Python and Bash scripting.
• Experience implementing CI/CD, monitoring and observability.
• Hands-on with cloud platforms (AKS, GKE) and cloud-native services.
• Understanding of distributed systems, scalability, reliability and performance tuning.

Responsibilities

• Design and deploy Kubernetes-based platforms for AI/ML, HPC and distributed workloads.
• Build, administer, and optimize HPC environments with schedulers like Slurm and Volcano.
• Deploy and sustain NVIDIA GPU infrastructure for ML and simulation workloads.
• Implement IaC, CI/CD and automation to scale platforms.
• Manage containerized apps using Kubernetes, Docker, Helm, and cloud tech.
• Troubleshoot and optimize cluster, network, storage, and app performance.

Skills

Kubernetes

Platform Engineering

Cloud Infrastructure

DevOps

SRE

Python

Bash scripting

CI/CD pipelines

Monitoring and observability

AKS/GKE

Tools

Docker

Helm

Slurm

Volcano

Terraform

Prometheus

Grafana

Azure AKS

GKE

Job description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s mostinnovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as theyprovide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days arethe same.

Location

This role is remote based in USA

About The Job You’re Considering

We are seeking an experienced Kubernetes / HPC Engineer with 5+ years of experience in Kubernetes, cloud infrastructure, and platform engineering to design, deploy, and support scalable compute platforms for AI/ML, simulation, and high-performance computing workloads. This role will focus on building reliable, secure, and high-performance infrastructure across cloud and on-premises environments while enabling next-generation AI, research, and data-intensive applications.

Your role

• Design, deploy, and manage Kubernetes-based platforms supporting AI/ML, HPC, and distributed computing workloads.
• Build, administer, and optimize HPC environments utilizing workload schedulers such as Slurm and Volcano.
• Deploy and support NVIDIA GPU infrastructure for machine learning, simulation, and accelerated computing workloads.
• Implement infrastructure automation, CI/CD pipelines, and Infrastructure-as-Code practices to improve platform scalability and operational efficiency.
• Manage containerized applications using Kubernetes, Docker, Helm, and cloud-native technologies.
• Troubleshoot and optimize cluster, network, storage, and application performance across distributed computing environments.

Your Skills And Experience

• 5+ years of experience in Kubernetes, Platform Engineering, Cloud Infrastructure, DevOps, Site Reliability Engineering, or related technical disciplines.
• 2+ years of experience supporting High-Performance Computing (HPC) environments, distributed computing platforms, or large-scale compute clusters.
• Strong hands-on expertise with Kubernetes, Docker, Helm, and container orchestration technologies.
• Experience managing HPC clusters and workload schedulers, including Slurm, Volcano, or similar scheduling platforms.
• Expertise with NVIDIA GPU infrastructure, GPU-enabled workloads, performance optimization, and accelerated computing environments.
• Strong Linux administration, troubleshooting, and automation skills, including Python and Bash scripting.
• Experience implementing CI/CD pipelines, monitoring, logging, observability, and infrastructure automation solutions.
• Hands-on experience with major cloud platforms, including Azure Kubernetes Service (AKS), Google Kubernetes Engine (GKE), or comparable cloud-native services.
• Strong understanding of distributed systems, cloud-native architectures, scalability, reliability, and performance tuning.

Good To Have Skills

• Experience supporting AI/ML platforms and large-scale model training workloads.
• Exposure to AWS Trainium, AWS Inferentia, or AI accelerator technologies.
• Experience with Infrastructure-as-Code tools such as Terraform.
• Knowledge of cloud networking, storage systems, and hybrid cloud architectures.
• Experience with observability platforms such as Prometheus and Grafana

The base compensation range for this role in the posted location is $76,730 to $150,800

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Benefits

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.

In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

Important Notice

Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.