Job Summary

Role Summary

Build, automate, and operate enterprise AI platforms and AI-native applications. Drive Platform Engineering, DevOps, MLOps/LLMOps, Kubernetes, Cloud, and GenAI solution delivery.

Key Responsibilities

• Design and develop AI applications, APIs, and microservices.
• Build and manage AI platforms on Azure/AWS/GCP and Kubernetes/OpenShift.
• Implement CI/CD, GitOps, Infrastructure as Code, and DevSecOps practices.
• Develop and operationalize MLOps/LLMOps pipelines.
• Deploy and manage LLMs, RAG solutions, vector databases, and AI services.
• Enable observability, reliability, security, and cost optimization for AI workloads.

Skill Requirements

• Python, FastAPI, REST APIs
• GenAI, RAG, LangChain/LangGraph
• Kubernetes/OpenShift, Docker
• Azure DevOps, GitHub Actions, Jenkins
• Terraform, ArgoCD, GitOps
• Azure/AWS/GCP
• PostgreSQL, Vector Databases
• Monitoring: Grafana, Prometheus, OpenTelemetry

Other Requirements

• Azure AI Foundry, Azure ML, Vertex AI
• MLflow, KServe, vLLM, NVIDIA AI Stack
• Agentic AI and Multi-Agent Systems