Lead AI Engineer- DevOps
INR 1800K-3440K (estimate) Senior-level Full Time
Tasks
- Automate releases
- Build cloud native infrastructure
- Create dashboards and alerts
- Deploy microservices and web applications
- Design CI/CD pipelines
- Enable AI ML workload deployment
- Ensure security, reliability, and compliance
- Implement deployment workflows
- Implement infrastructure-as-code
- Implement model serving monitoring
- Improve observability
- Maintain runbooks and rollback mechanisms
- Manage secrets and access control
- Mentor engineers and provide accelerators
- Operate runtime platforms
- Run incident response and root cause analysis
- Set up logs metrics traces
- Standardize build automation and release quality
- Standardize environments
- Support containerized services
- Use distributed tracing
Perks/Benefits
- N/A
Skills/Tech-stack
AI Studio | AKS | API Gateway | Access Management | Application Insights | Authentication | Azure | Azure AI | Azure AI Studio | Azure Container | Azure Container Apps | Azure Container Registry | Azure DevOps | Azure Functions | Azure Machine Learning | Azure Monitor | Azure OpenAI | Bicep | CI/CD | Cloud Computing | Container Apps | Container Registry | Datadog | Distributed tracing | Docker | Event Driven | Event-driven architecture | GitHub | GitHub Actions | Grafana | Identity and Access Management | Identity and access | Incident Response | Infrastructure as Code | Kubernetes | Log Analytics | Logging | Machine Learning | Microservices | Monitoring | New Relic | OpenAPI | OpenTelemetry | Prometheus | PromptFlow | REST | Rollback | Runbooks | Secrets management | Terraform | “as-code”
Education
N/A
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