We are seeking a hands-on Senior Cloud DataOps & MLOps Engineer to build, manage, and optimize modern AWS-based cloud, monitoring, and ML platform environments. The role focuses on enabling scalable observability, centralized monitoring, cloud automation, and MLOps capabilities using AWS services and enterprise monitoring tools.
The ideal candidate will have strong experience in AWS cloud engineering, monitoring platforms, infrastructure automation, and production support within enterprise environments.
Key Responsibilities
- Design, implement, and manage AWS cloud infrastructure and operational platforms
- Configure and support Amazon SageMaker environments for ML platform enablement
- Implement centralized monitoring, metrics, and alerting using Prometheus and Grafana
- Build and maintain logging and observability pipelines across AWS services and applications
- Develop operational dashboards, monitoring standards, and alerting frameworks
- Support Infrastructure-as-Code (IaC) and CI/CD automation initiatives
- Collaborate with application, data, and platform teams to improve reliability and operational visibility
- Troubleshoot production issues and optimize platform performance and stability
- Ensure adherence to cloud security, governance, and operational best practices
Required Skills & Experience
Mandatory Skills
- Strong hands-on experience with AWS cloud platforms
- Good knowledge of:
- IAM
- VPC
- EC2
- S3
- CloudWatch
- ECS/EKS
- Cloud security and networking fundamentals
- Experience with:
- Prometheus
- Grafana
- Monitoring and observability platforms
- Centralized logging architectures
- Experience with Amazon SageMaker or MLOps platforms
- Hands-on experience with Terraform, CloudFormation, or similar IaC tools
- Scripting experience using Python or Bash
- Experience supporting enterprise production cloud environments
Preferred Skills
- Kubernetes/EKS experience
- OpenTelemetry knowledge
- CI/CD pipeline implementation experience
- DataOps or Platform Engineering background
- AWS certifications
