AWS Trainium / AI Infrastructure Engineer

Capgemini; Atlanta (GA); A distancia; USD 77.000 - 151.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

PTO

Medical coverage

Retirement plans

Life insurance

EAP

Descripción de la vacante

Capgemini Engineering is seeking an experienced AI Infrastructure Engineer to design and operate scalable AI infrastructure on AWS, enabling large-scale model training and inference for Generative AI and LLM initiatives.

The role emphasizes containerized, cloud-native platforms using Kubernetes, Docker, and IaC, with collaboration across AI engineers and data scientists to ensure reliable model development and deployment.

Formación

• 5+ years of experience in Cloud/Platform/Data AI infrastructure or related domains.
• Strong experience with large-scale AWS AI/ML training and inference.
• Hands-on with AWS Trainium, Inferentia, EC2 Trn, and Neuron SDK.

Responsabilidades

• Design, deploy, and manage scalable AI/ML infrastructure on AWS.
• Support distributed model training and inference for LLMs and Generative AI.
• Optimize AI workloads for performance, scalability, and cost.

Conocimientos

AI infrastructure

Cloud engineering

Platform engineering

Data engineering

AWS

Kubernetes

Docker

Python

PyTorch

MLOps

IaC

Herramientas

AWS Trainium

AWS Inferentia

SageMaker

EKS

EC2 Trn instances

Descripción del empleo

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 AI Infrastructure Engineer with 5+ years of experience in cloud, AI/ML, and platform engineering to design and operate scalable AI infrastructure on AWS. This role will focus on enabling large-scale model training and inference, optimizing AI workloads, and building cloud-native platforms that support Generative AI and Large Language Model (LLM) initiatives using AWS AI acceleration technologies.

Your role

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

Your Skills And Experience

• 5+ years of experience in Cloud Engineering, Platform Engineering, Data Engineering, AI Infrastructure, or related technical domains.
• Strong experience supporting large-scale AI/ML training and inference workloads within AWS environments.
• Hands‑on experience with AWS Trainium, AWS Inferentia, EC2 Trn instances, and AWS Neuron SDK for accelerated AI model training and inference.
• Strong understanding of Large Language Models (LLMs), Generative AI, distributed training architectures, and AI/ML infrastructure design.
• Expertise with Amazon EKS, Kubernetes, Docker, and cloud‑native platform engineering practices.
• Proficiency in Python, PyTorch, MLOps, Infrastructure as Code (IaC), and AI workload automation.
• Experience optimizing AI platform performance, benchmarking model workloads, and migrating workloads from GPU-based environments to AWS AI accelerators.

Preferred Qualifications

• Experience with Amazon SageMaker and enterprise‑scale MLOps platforms.
• Experience deploying and supporting foundation models and Generative AI workloads in production environments.
• Knowledge of distributed computing frameworks and high-performance AI infrastructure.
• Experience implementing observability, monitoring, security, and governance solutions for AI platforms.
• AWS certifications related to Machine Learning, Solutions Architecture, or Cloud Engineering.

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.