About the Role:
We are seeking an AWS DevOps / MLOps Engineer to support our Agentic AI projects.
The role involves building, automating, and managing cloud infrastructure and machine learning workflows on AWS, ensuring smooth deployment and operation of AI solutions.
Key Responsibilities:
- Design, deploy, and manage AWS infrastructure (VPC, EC2, ECS/EKS, S3, IAM, Lambda, Step Functions).
- Build and maintain CI/CD pipelines for deploying applications, data pipelines, and ML models.
- Apply MLOps practices to automate model versioning, training, testing, deployment, and monitoring.
- Use AWS SageMaker to manage model training, deployment, monitoring, and drift detection.
- Automate data and ML workflows using Airflow, Step Functions, or Kubeflow.
- Set up monitoring and alerting using tools like CloudWatch, Prometheus, or Grafana.
Required Skills & Qualifications:
- 3+ years of experience in DevOps, Cloud Engineering, or MLOps.
- Strong knowledge of AWS services: SageMaker, S3, EKS/ECS, Lambda, API Gateway, Redshift, DynamoDB, Step Functions.
- Experience with CI/CD tools like Jenkins, GitHub Actions, GitLab CI/CD, or AWS CodePipeline.
- Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, AWS CDK).
- Good scripting skills in Python, Bash, or Go.
- Familiarity with Docker, Kubernetes, and container orchestration.
- Understanding of ML model lifecycle: data ingestion, training, deployment, monitoring, retraining.
- Experience with monitoring and logging tools (CloudWatch, ELK, Prometheus, Datadog).
- Knowledge of GitOps practices to manage infrastructure and ML models.
Education
Bachelor Of Computer Application (B.C.A), Master of Health Science (MHSc), Post Graduate Diploma in Computer Applications (PGDCA), Master in Computer Application (M.C.A), Master in Landscape Architecture, Doctor of Public Health (DrPH)
Skills Required
Cloud Engineering, S3, Lambda, Api Gateway, Redshift, Dynamodb, Cloudformation, Bash, Kubernetes, Training, Deployment, Monitoring, Elk, Prometheus