Required Skillset: Azure AI foundary, LLM, observability, RAG, vector DB
Location: PAN INDIA
Experience Range: 8+ years
:
Design, build and operate scalable cloud automation across AWS and Azure enabling secure and standardized adoption.
Required Skills & Qualifications:
- LangGraph
- LangChain
- Semantic Kernel
- Azure AI Foundry
- Azure OpenAI
- RAG
- Multi-Agent Systems
- MCP
- AI Observability
- LLMOps
- Prompt Flow
- Azure AI Search
- Agentic AI
- Copilot Studio
- Vector Databases
- AI Governance
- AI Guardrails
- GenAI Solution Design
Key Responsibilities:
Cloud automation engineering
- Design and implement automation for cloud service provisioning (AWS and Azure)
- Develop and maintain infrastructure as code (IaC) using Terraform or similar tools
- Build and enhance automation APIs, scripts, and workflows
- Contribute to shared automation frameworks and reusable components
Platform and landing zone enablement
- Support and evolve cloud landing zone capabilities, including account/subscription setup
- Implement and maintain “Day One” baseline configurations (networking, security, IAM)
- Troubleshoot and remediate non-standard or legacy cloud environments
- Ensure adherence to enterprise standards for security, tagging, and governance
DevOps and CI/CD integration
- Develop and maintain CI/CD pipelines (GitLab preferred)
- Manage repositories, merge requests, and release workflows
- Enable self-service automation for engineering teams
Cloud operations and support
- Provide advanced troubleshooting across:
- IAM roles and permissions
- Networking (VPC, DNS, private endpoints)
- Automation execution failures
- Support onboarding of current cloud accounts and workloads
- Partner with engineering and operations teams to resolve production issues
Cross-team collaboration
- Work closely with:
- Cloud architects
- Security and compliance teams
- Platform engineering teams
- Translate requirements into scalable automation solutions
- Contribute to documentation, standards, and best practices