AI-Powered AWS Full-Stack Engineer

ManpowerGroup Global, Inc.; Malvern (AR); On-site; USD 85,000 - 110,000; Full time

Benefits offered by this job

Medical plan

Dental plan

Vision plan

HSA

FSA

401(k) with match

Weekly pay

Job summary

Our client in the technology and innovation sector seeks an AWS Full Stack Engineer to support the development and deployment of cloud-native AI-powered applications. The role requires collaboration across teams to deliver secure, scalable solutions using AWS services and modern DevOps practices.

The candidate will work on design, development, and deployment of AI pipelines, integrating foundation models, and ensuring production-grade security and reliability in a fast-paced environment.

Qualifications

• Extensive experience in full-stack development (frontend and backend).
• Hands-on AWS experience including SageMaker, Bedrock, Rekognition, Textract, Transcribe, Translate and core cloud infra.
• Proficiency in Python backend development.
• Experience with containers (Docker) and orchestration (ECS/EKS).
• Strong understanding of scalable, resilient production systems.

Responsibilities

• Design, develop, and deploy AI-powered applications on AWS.
• Integrate foundation models and LLMs into scalable applications.
• Build and optimize AI pipelines for inference and fine-tuning.
• Implement security best practices including IAM and VPC design.
• Collaborate with cross-functional teams to operationalize AI features.

Skills

Full-stack development

AWS services

Python

Docker

ECS/EKS

Security best practices

Tools

Docker

SageMaker

Bedrock

Rekognition

Textract

Transcribe

Translate

IAM

VPC

EC2

Job description

Our client in the technology and innovation sector seeks an AWS Full Stack Engineer to support the development and deployment of cloud-native AI-powered applications. The role requires collaboration across teams to deliver secure, scalable solutions using AWS services and modern DevOps practices.

The candidate will work on design, development, and deployment of AI pipelines, integrating foundation models, and ensuring production-grade security and reliability in a fast-paced environment.