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
