Role:- AWS Devops AI Engineer

We are looking for a highly skilled DevOps / MLOps Engineer with 5+ years of experience to build and manage scalable infrastructure and enable robust AI/ML deployment pipelines on AWS.

Key Responsibilities:

Design and manage scalable cloud infrastructure on AWS (EC2, EKS, Lambda, S3, VPC, IAM, CloudWatch, CloudFormation/Terraform)
Build and maintain CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI for seamless deployments
Deploy and manage containerized applications using Docker and Kubernetes (EKS preferred)
Implement monitoring, logging, and alerting frameworks using CloudWatch, Prometheus, and Grafana
Build, deploy, and monitor Machine Learning models using AWS SageMaker, Bedrock, and open-source frameworks (TensorFlow, PyTorch, Scikit-learn)
Develop and automate ML pipelines for training, validation, and production deployment
Optimize model performance and inference at scale across distributed environments
Collaborate with data engineering teams to integrate AI/ML models into data pipelines

Key Requirements:

5+ years of experience in DevOps / MLOps / Cloud Engineering roles
Strong expertise in AWS ecosystem and infrastructure automation
Hands-on experience with Docker, Kubernetes (EKS), and Infrastructure as Code tools
Experience building CI/CD pipelines and release automation workflows
Proficiency in ML lifecycle management and deployment pipelines
Strong understanding of monitoring, logging, and system reliability best practices

Good to Have:

Exposure to GenAI / LLM deployment (Bedrock or open-source models)
Experience with model serving frameworks (FastAPI, TorchServe, etc.)
Familiarity with data pipelines and distributed systems

Education:- B.E/B.Tech/MCA only

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