DevOps Engineer (all genders)
Tasks
- Automate infrastructure using Infrastructure as Code
- Build CI/CD pipelines
- Configure autoscaling and ingress
- Create dashboards and alerts
- Define SLO SLA and service readiness guardrails
- Deploy and manage container workloads on Kubernetes
- Design secure cloud infrastructure for GenAI applications
- Enable safe model fine tuning pipelines
- Implement artifact management and environment promotion
- Implement incident response and on call readiness
- Manage cloud networking and security policies
- Set up observability with metrics logs tracing
- Support MLOps LLMOps evaluation and deployment workflows
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Amazon Elastic Kubernetes Service | Autoscaling | Azure | Azure Kubernetes | Azure Kubernetes Service | Azure Virtual | Azure Virtual Network | Bicep | CI/CD | Cloud Networking | CloudFormation | Containerization | Distributed tracing | Elastic Kubernetes Service | Fine Tuning | GPU Workflows | Google Cloud | Google Kubernetes | Google Kubernetes Engine | IAM | Image security | Incident Management | Infrastructure as Code | Ingress | KMS | Key Vault | Kubernetes | Kubernetes Engine | Kubernetes Service | Logging | MLOps | MLflow | Metrics | Model Evaluation | Model Fine-tuning | Model Registry | Observability | On-Call | Postmortems | Private Endpoints | Runbooks | SLA | SLO | Service Mesh | Terraform | VPC | Virtual Network | “as-code”
Education
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