Data Engineer
Tasks
- Build and operate ML and LLM pipelines
- Create and maintain monitoring with Prometheus and OpenTelemetry
- Deploy services on AWS and Azure
- Design maintain evolve AIOps platform
- Implement LLMOps and AgentOps practices
- Manage deployments with Docker and Kubernetes
- Manage infrastructure as code
- Manage prompt management and traceability
- Monitor model and LLM quality and drift
- Operate dashboards alerts and SLOs
- Run CI/CD pipelines
- Scale AI products and implement auto remediation
- Set up reliability automation and observability
Perks/Benefits
- N/A
Skills/Tech-stack
AI Agents | AWS | Airflow | Argo | Azure | Azure DevOps | Azure ML | CI/CD | CloudWatch | Docker | EFK | ELK | GitHub Actions | GitLab CI | Grafana | Infrastructure as Code | Jenkins | Kubernetes | LLM Evaluation | LLM Observability | Langchain | Llamaindex | ML model monitoring | MLflow | Model Monitoring | OpenTelemetry | Prometheus | Prompt management | Python | RAG | SageMaker | Semantic Kernel | Step Functions | Terraform | Workflow Orchestration | “as-code”
Education
N/A
Roles
AIOps Engineer | AgentOps Engineer | Engineer | LLMOps Engineer | MLOps Engineer
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