Nothing can limit your
dreams when you are at
Zoft

Work Location : Kochi, Kerala

About the Role

We are looking for a talented AWS DevOps/MLOps Engineer to support our Agentic AI initiative. This role will focus on designing, automating, and maintaining scalable infrastructure and ML workflows in AWS.

Key Responsibilities

• Design and manage AWS infrastructure (VPC, EC2, ECS/EKS, S3, IAM, Lambda, Step Functions, CloudFormation/Terraform).
• Build and maintain CI/CD pipelines for AI/ML models, data pipelines, and applications.
• Implement MLOps practices (versioning, automated training, testing, deployment, and monitoring of ML models).
• Work with AWS SageMaker for model training, deployment, monitoring, and drift detection.
• Automate data and ML workflows using tools like Airflow, Step Functions, or Kubeflow.
• Enable observability and monitoring with CloudWatch, Prometheus, Grafana, or similar tools.

Required Skills & Qualifications

• 4-8 years of experience in DevOps, Cloud Engineering, or MLOps (depending on seniority).
• Strong expertise in AWS services (SageMaker, S3, EKS/ECS, Lambda, API Gateway, Redshift, DynamoDB, Step Functions).
• Hands-on experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI/CD, AWS CodePipeline).
• Proficiency with IaC tools (Terraform, AWS CDK, or CloudFormation).
• Strong skills in Python, Bash, or Go scripting.
• Familiarity with Docker, Kubernetes, and container orchestration.
• Knowledge of ML lifecycle management (data ingestion, model training, deployment, monitoring, retraining).
• Experience with monitoring and logging frameworks (CloudWatch, ELK, Datadog, Prometheus).
• Understanding of GitOps practices for managing infrastructure and ML models.