AWS DevOps/MLOps Engineer (Agentic AI – AWS)

Job Title: AWS DevOps/MLOps Engineer (Agentic AI – AWS)

Experience: 6+ Years

Location: Remote

Budget: ₹1.10 LPM + GST

Job Summary

We are looking for an experienced AWS DevOps/MLOps Engineer to support an Agentic AI initiative. The ideal candidate should have strong hands-on experience with AWS infrastructure, DevOps automation, CI/CD, MLOps practices, and production deployment of AI/ML workloads.

The candidate will be responsible for designing, automating, deploying, and maintaining scalable infrastructure and machine learning workflows on AWS.

Key Responsibilities

• Design, provision, and manage scalable AWS infrastructure.
• Work with AWS services including:
• VPC
• EC2
• ECS / EKS
• S3
• IAM
• Lambda
• Step Functions
• Implement Infrastructure as Code using Terraform and/or AWS CloudFormation.
• Build and maintain CI/CD pipelines for AI/ML models, applications, and data pipelines.
• Implement end-to-end MLOps practices, including:
• Model and artifact versioning
• Automated training
• Automated testing
• Model deployment
• Model monitoring
• Work with AWS SageMaker for model training, deployment, monitoring, and drift detection.
• Automate ML and data workflows using tools such as Airflow, AWS Step Functions, or Kubeflow.
• Build scalable deployment pipelines for Agentic AI and machine learning applications.
• Implement infrastructure and application monitoring using:
• AWS CloudWatch
• Prometheus
• Grafana
• Troubleshoot infrastructure, deployment, and ML pipeline issues.
• Ensure AWS infrastructure follows security, scalability, reliability, and DevOps best practices.

Mandatory Skills

• 6+ years of relevant DevOps / Cloud / MLOps experience.
• Strong hands-on experience with AWS.
• Experience with EC2, VPC, IAM, S3, Lambda, ECS and/or EKS.
• Strong knowledge of CI/CD pipeline development and automation.
• Hands-on experience with Terraform and/or CloudFormation.
• Experience implementing MLOps workflows.
• Hands-on experience with AWS SageMaker.
• Experience with model training, deployment, monitoring, and drift detection.
• Experience automating data/ML workflows using Airflow, Step Functions, or Kubeflow.
• Good understanding of containerization and orchestration.
• Experience with observability and monitoring tools such as CloudWatch, Prometheus, and Grafana.
• Strong troubleshooting and problem-solving skills.

Preferred Skills

• Experience supporting Generative AI / Agentic AI workloads.
• Experience deploying AI/ML applications in production environments.
• Strong knowledge of Docker and Kubernetes.
• Experience managing scalable and secure cloud infrastructure.
• Understanding of model lifecycle management and production ML systems.

Ideal Candidate

We are looking for a hands-on AWS DevOps/MLOps Engineer who can independently build and manage cloud infrastructure, CI/CD pipelines, ML workflows, and production AI/ML deployments.

Candidates with strong experience in AWS, SageMaker, Terraform, Kubernetes, CI/CD, MLOps, Airflow/Step Functions, and monitoring will be preferred.

Interested candidates can share their updated resume at

hire@kasmoprav.com

Email Subject: AWS DevOps/MLOps Engineer – Agentic AI

Pay: ₹80,000.00 - ₹90,000.00 per month

Work Location: Remote