AWS AI Lead Engineer
Tasks
- Apply FinOps cost optimization
- Apply IAM best practices and secrets management
- Build AI assisted anomaly detection and root cause analysis
- Build agent driven operational workflows
- Build containerized workloads
- Build reusable platform components
- Define monitor SLOs SLIs and error budgets
- Design CI/CD pipelines
- Design scalable AWS infrastructure
- Drive reliability engineering practices
- Embed security into CI/CD pipelines
- Enable self service platforms
- Ensure enterprise compliance
- Generate automation scripts using AI tools
- Implement GitOps workflows
- Implement multi account multi region governance
- Implement observability with dashboards and alerts
- Implement progressive delivery
- Implement self-healing automation
- Implement zero trust principles
- Improve developer experience
- Integrate automated testing and security scanning
- Maintain end to end release pipelines
- Manage Kubernetes clusters
- Optimize cluster performance and cost
- Use AWS Bedrock for automation
Perks/Benefits
- N/A
Skills/Tech-stack
AWS CDK | AWS IAM | Amazon EKS | Amazon Web Services | Argo CD | Blue/green | CI/CD | Canary | CloudFormation | CloudWatch | DevSecOps | Docker | Docker Image | Docker Image Scanning | Error budget | Feature Flags | FinOps | Flux | GitHub Actions | GitOps | Grafana | Harness | Image scanning | Infrastructure as Code | Jenkins | Kubernetes | OpenTelemetry | Prometheus | SLI | SLO | Secrets management | Security Compliance | Snyk | SonarQube | Terraform | Trivy | Veracode | Web Services | Zero Trust | “as-code”
Education
N/A
Roles
AI | AI Engineer | Cloud Engineer | Cloud) | DevOps | DevOps Engineer | Engineer
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