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# AWS Cloud SRE - AI/ML Platform

- **Company:** Brooksource
- **Location:** Maryland Heights, United States (Remote available)
- **Experience:** Expert
- **Salary:** $145,600.0 - $166,400.0
- **Contract:** Temporary to permanent
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Bash Shell, Cloud Computing, Cloud Engineering, Continuous Integration, DevOps, Fraud Prevention and Detection, Graph Database, Identity and Access Management, Python (Programming Language), Key Management, Machine Learning, Reliability Engineering, Azure Machine Learning, Scripting, Large Language Models, Amazon Virtual Private Cloud (VPC), Amazon Relational Database Service, Containerization, Kubernetes, Machine Learning Operations, Cloudwatch, Terraform, Serverless Computing
- **Published:** August 28, 2026
- **Apply:** https://www.dice.com/job-detail/4784aeb6-1038-4af5-b5a5-78a4342b7e09

## About the Role

* 8+ years of overall technical experience, including 3+ years in SRE, DevOps, Cloud Administration, or Cloud Engineering roles within production AWS environments
 * Deep hands-on AWS experience with services such as EC2, VPC, IAM, S3, RDS, EKS/ECS, Lambda, CloudWatch, and CloudTrail
 * Strong Infrastructure-as-Code and automation skills using Terraform and scripting (Python, Bash, or similar)
 * Hands-on experience operating Kubernetes/EKS workloads, including scaling, networking, deployment, and secrets management
 * Working knowledge of the machine-learning lifecycle and production experience with SageMaker, Bedrock, or comparable AI/ML platforms
 * Experience supporting production AI/ML, GenAI, LLM/RAG, or classical ML services with observability, reliability, and operational controls
 * Demonstrated ownership mindset, taking technical requirements through implementation, integration, deployment, and ongoing support

## Description

Brooksource is seeking a Senior AWS Cloud Site Reliability Engineer (SRE) - AI/ML Platform to join a high-impact Fraud Prevention AI/ML Engineering Team within a Fortune 500 telecommunications client. In this contract role, you will own and enhance AWS infrastructure, automation, reliability, and production environments supporting modern AI/ML and GenAI workloads. You will operate at the intersection of traditional SRE/cloud engineering and modern MLOps/LLMOps, enabling teams to move AI applications and models into reliable, scalable production environments. The broader program includes agentic AI and anomaly-detection capabilities, leveraging technologies such as SageMaker, Bedrock, graph-based solutions, RAG, and other machine-learning services. This engagement is expected through the end of 2026, with potential for extension based on performance and business needs. You will have the opportunity to contribute to a high-visibility, new-build AI/ML initiative and work alongside
talented engineers in a dynamic, relationship-driven environment.

WHAT YOU'LL DO

 * Design, operate, and support scalable AWS infrastructure powering production AI/ML, GenAI, and anomaly-detection workloads
 * Administer and automate AWS services across networking, compute, identity, storage, containers, serverless, monitoring, and security
 * Collaborate with AI/ML and application engineers to productionize models, ML pipelines, LLM/RAG solutions, and other AI-driven services
 * Build and maintain infrastructure automation using Terraform and CI/CD, supporting containerized workloads on Kubernetes/EKS and related services
 * Enhance platform reliability through monitoring, observability, incident response, troubleshooting, scaling, operational automation, and post-deployment validation
 * Support AI/ML platform capabilities involving SageMaker, Bedrock, graph databases, vector databases, and retrieval-based architectures
 * Ensure operational controls and best practices for production AI/ML, GenAI, and classical ML services
 * Take ownership of technical requirements from implementation through integration, deployment, and ongoing support


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