Cloud Platform Engineer

The Cloud Platform Engineer will support a high-impact initiative to reduce SNAP payment errors by building and optimizing secure scalable AWS-based AI and data platforms. This role requires a senior-level engineer (7 years AWS) with deep expertise in cloud infrastructure AI/ML (SageMaker Bedrock LLM agents) data pipelines and MLOps who can design fault-tolerant architectures automate infrastructure with IaC deploy intelligent agent-based workflows and ensure performance compliance and operational excellence across production environments.

This is an ongoing contract hybrid role (three days onsite/ two days remote).

Tasks & Duties:

• Monitor database and system performance using CloudWatch metrics alarms and logs; troubleshoot proactively.
• Develop deploy and optimize AI/ML solutions using AWS AI services including SageMaker and Bedrock supporting model training inference and integration into production systems.
• Automate operational tasks using AWS Lambda Systems Manager (SSM) and Infrastructure-as-Code tools such as CloudFormation or Terraform.
• Design build and maintain scalable fault-tolerant data processing and analytics workflows on AWS using services such as API Gateway S3 EC2 RDS Lambda Glue Athena DynamoDB EMR Kinesis DataSync.
• Design and integrate agentic AI systems including LLM-based agents multi-agent workflows and autonomous orchestration pipelines using frameworks such as LangChain and LangGraph.
• Implement ETL/ELT pipelines and data architectures that support machine learning analytics and intelligent agent-based applications.
• Support CI/CD pipelines for AI models and data workflows using Jenkins and container-based platforms such as ECS EKS or Kubernetes.
• Apply security best practices across AI and data platforms including IAM least-privilege access encryption audit logging and compliance controls.
• Maintain technical documentation for AI architectures data pipelines infrastructure configurations and operational runbooks.

Required Skills

• Minimum 7 years of hands-on AWS experience: EC2 RDS S3 CloudWatch CloudTrail IAM KMS AWS Backup and Lambda.
• Minimum 7 years of experience in Linux/Unix administration and automation scripting (Bash Shell Python).
• Minimum 7 years of experience with Infrastructure as Code (IaC) and automation tools including CloudFormation Terraform and Ansible for provisioning and maintaining.
• Minimum 7 years of knowledge in AWS networking: VPC subnets NACLs security groups Route 53 and multi-AZ architectures.
• Minimum 5 years of experience CI/CD pipelines Jenkins and IaC for deploying AI agents and ML models into production monitoring autonomous workflows and supporting MLOps using Kubernetes ECS or EKS.
• Minimum 4 years of experience architecting building and maintaining scalable data processing workflows using AWS managed services and Python (including PySpark); strong understanding of data architecture and ETL/ELT patterns.
• Minimum 4 years of experience working with AWS AI/ML services such as SageMaker Bedrock and vector databases (OpenSearch).
• Strong understanding of machine learning algorithms NLP concepts and deep learning frameworks such as TensorFlow PyTorch or Hugging Face.