AWS Trainium / AI Infrastructure Engineer

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

Benefits offered by this job

Paid time off

Healthcare coverage

401(k) retirement plan

Life and disability insurance

Employee assistance programs

Job summary

Capgemini Engineering is seeking an experienced AI Infrastructure Engineer to design and manage scalable AI/ML infrastructure on AWS, leveraging Trainium, Inferentia, SageMaker, and EKS.

The role supports distributed model training and inference for LLMs and Generative AI, focusing on performance, cost efficiency, and cloud-native, containerized solutions. It is remote anywhere in the USA, with a strong emphasis on reliability and collaboration with AI teams.

Qualifications

• 5+ years in Cloud, Data, or AI Infrastructure.
• Experience supporting large-scale AI/ML training workloads in AWS.
• Exposure to Trainium or Inferentia is highly preferred.
• Experience with AWS Trainium, Inferentia, EC2 Trn instances, and AWS Neuron SDK for AI model training and inference.
• Strong understanding of LLMs, Generative AI, distributed training, and AI/ML infrastructure.
• Hands-on experience with Kubernetes (EKS), Docker, Python, PyTorch, and cloud-native architecture.

Responsibilities

• Design, deploy, and manage scalable AI/ML infrastructure on AWS using Trainium, Inferentia, SageMaker, and EKS.
• Support distributed model training, inference, and deployment for LLMs and Generative AI applications.
• Optimize AI workload performance, resource utilization, and cost efficiency across cloud environments.
• Implement containerized and cloud-native solutions using Kubernetes, Docker, and Infrastructure-as-Code practices.
• Collaborate with AI engineers and data scientists to enable reliable, high-performance model development and deployment pipelines.
• Monitor, troubleshoot, and improve platform reliability, scalability, and operational excellence.
• Evaluate and implement emerging AI infrastructure technologies to support future business and technology initiatives.

Skills

5+ years

AWS cloud

Kubernetes (EKS)

Docker

Python

PyTorch

AWS Trainium/Inferentia

SageMaker

LLM/Generative AI

Tools

Trainium

Inferentia

AWS Neuron SDK

EC2 Trn instances

Job description

Location

This role is remote anywhere in USA

About The Job You're Considering

We are looking for an experienced AI Infrastructure Engineer with expertise in AWS cloud, large-scale AI/ML platforms, and distributed model training. The candidate should have hands-on experience with AWS Trainium/Inferentia, AWS Neuron SDK, SageMaker, EKS/Kubernetes, and scalable AI infrastructure. AWS positions Trainium as a purpose-built accelerator for AI training and inference at scale.

Your role

• Design, deploy, and manage scalable AI/ML infrastructure on AWS using Trainium, Inferentia, SageMaker, and EKS.
• Support distributed model training, inference, and deployment for Large Language Models (LLMs) and Generative AI applications.
• Optimize AI workload performance, resource utilization, and cost efficiency across cloud environments.
• Implement containerized and cloud-native solutions using Kubernetes, Docker, and Infrastructure-as-Code practices.
• Collaborate with AI engineers and data scientists to enable reliable, high-performance model development and deployment pipelines.
• Monitor, troubleshoot, and improve platform reliability, scalability, and operational excellence.
• Evaluate and implement emerging AI infrastructure technologies to support future business and technology initiatives.

Your Skills And Experience

• 5+ years in Cloud, Data, or AI Infrastructure.
• Experience supporting large-scale AI/ML training workloads in AWS environments.
• Exposure to Trainium or Inferentia is highly preferred.
• Experience with AWS Trainium, Inferentia, EC2 Trn instances, and AWS Neuron SDK for AI model training and inference.
• Strong understanding of LLMs, Generative AI, distributed training, and AI/ML infrastructure.
• Hands-on experience with Kubernetes (EKS), Docker, Python, PyTorch, and cloud-native architecture.
• Experience in AI performance optimization, benchmarking, and migration from GPU-based environments to AWS AI accelerators.

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.

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.