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AWS DevOps/MLOps Engineer (Agentic AI – AWS)

Kasmoprav
Remote

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Job details

Contractual / Temporary
₹80,000 - ₹90,000 a month

Qualifications

CI/CD
Cloud infrastructure
Kubernetes
Software deployment
DevOps
AWS
Docker
Machine learning
Terraform
Continuous integration
S3
AI
Identity & access management
AWS CloudFormation

Full job description

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:
[email protected]

Email Subject: AWS DevOps/MLOps Engineer – Agentic AI

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

Work Location: Remote

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