Senior Site Reliability Engineer - AI Platform
INR 3000K-5000K (estimate) Senior-level Full Time
Tasks
- Build observability monitoring logging tracing alerting
- Collaborate with AI ML data platform and cloud teams
- Define SLIs SLOs error budgets
- Deploy and manage Kubernetes environments
- Deploy model serving and inference endpoints
- Ensure performance optimization and reliability
- Implement SRE practices
- Implement infrastructure as code and automation
- Implement security controls IAM RBAC secrets encryption secure networking
- Manage CI CD deployment automation
- Monitor platform health and reliability risks
- Operate AI platform services
- Optimize scalability load balancing autoscaling and resource utilization
- Perform incident response troubleshooting RCA and postmortems
- Support MLOps LLMOps and agentic ops model lifecycle monitoring
- Support governance compliance and auditability
Perks/Benefits
- N/A
Skills/Tech-stack
ADLS | API Gateway | AWS | Amazon SageMaker | Argo CD | Auto Scaling | Azure | Azure Machine Learning | Bash | CI/CD | Datadog | Disaster Recovery | Docker | ELK | Encryption | Envoy | Event Hubs | FastAPI | GCP | GCS | GitHub Actions | GitLab CI | GitOps | Grafana | IAM | Inference Server | Infrastructure as Code | Istio | Jenkins | KMS | KServe | Kafka | Kong | Kubeflow | Kubernetes | Langchain | Langgraph | Linkerd | Linux | Load Balancing | MLflow | Machine Learning | Nginx | OpenTelemetry | Powershell | Prometheus | Pub/Sub | Python | RBAC | Ray Serve | Reliability Engineering | S3 | Secrets management | Site Reliability | Site Reliability Engineering | Terraform | Triton Inference | Triton Inference Server | Vault | Vertex AI | “as-code”
Education
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