V Group Inc.For more details, please connect with Hiba Kidwai at or email at
start dates upon award up to a maximum of thirty-six (36) months
No. of Hours- 40/hrs
We are seeking a skilled Cloud Platform Engineer to support the SNAP Payment Error Rate (CAP) Reduction initiative. This role is responsible for designing, building, and operating scalable, secure, and highly available cloud-based data and AI platforms on AWS.
The engineer will play a key role in enabling data processing, analytics, machine learning, and agentic AI solutions that improve program accuracy, compliance, and operational efficiency.
Strong experience designing and operating cloud platforms on AWS.
Hands-on experience with AI/ML services, data engineering, and analytics workflows in cloud environments.
Experience with Infrastructure-as-Code, automation, and CI/CD pipelines.
Proficiency with containerization and orchestration platforms (Docker, ECS, EKS, Kubernetes).
Solid understanding of cloud security, IAM, encryption, logging, and compliance best practices.
Strong troubleshooting, documentation, and communication skills.
Experience supporting government, public sector, or compliance-driven systems.
Experience with LLM-based systems, agentic AI, or autonomous workflows.
Familiarity with large-scale data processing and analytics platforms.
Monitor and optimize database and system performance using AWS CloudWatch metrics, alarms, and logs, proactively identifying and resolving performance and reliability issues.
Design, develop, deploy, and optimize AI/ML solutions using AWS AI services such as SageMaker and Amazon Bedrock, supporting model training, inference, and production integration.
Automate operational and maintenance tasks using AWS Lambda, AWS Systems Manager (SSM), and Infrastructure-as-Code (IaC) tools including CloudFormation and Terraform.
Design, build, and maintain scalable, fault-tolerant data processing and analytics workflows using AWS services such as API Gateway, S3, EC2, RDS, Lambda, Glue, Athena, DynamoDB, EMR, Kinesis, and 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 and support ETL/ELT pipelines and data architectures that enable 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, and Kubernetes.
Apply security and compliance best practices across AI and data platforms, including IAM least-privilege access, encryption at rest and in transit, audit logging, and regulatory controls.
Develop and maintain technical documentation, including AI architectures, data pipelines, infrastructure configurations, and operational runbooks.Collaborate with cross-functional teams including data scientists, analysts, security teams, and program stakeholders to deliver reliable and compliant cloud solutions.
Government Administration and Health and Human Services
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