GenAI / Agentic AI
Hands-on GenAI and Agentic AI delivery experience.
Must have shipped production-grade solutions using LLMs such as OpenAI, Anthropic, or Azure OpenAI, not just POCs.
Hands-on experience with agentic frameworks such as LangGraph, LangChain, AutoGen, or CrewAI.
Python & AI Orchestration
Robust Python development experience.
FastAPI and asynchronous programming patterns.
RAG pipeline design and implementation.
Vector databases such as FAISS, Pinecone, or pgvector.
Prompt engineering and LLM evaluation.
Human-in-the-loop (HITL) workflow design.
Exposure to n8n or similar workflow automation tools is an added advantage.
Cloud & Enterprise Deployment
Hands-on experience with Azure services such as Azure OpenAI, Container Apps, Blob Storage, Key Vault, and Entra ID/RBAC, or equivalent AWS/GCP services.
Secure credential management and managed identity.
Enterprise integration experience with platforms/APIs such as Microsoft Graph API, Power Automate, Salesforce, ServiceNow, etc.
Agentic AI Architecture
Experience designing multi-agent systems.
Tool/function calling, memory, planning, state management, guardrails and observability.
HITL approval/escalation gates.
Ability to explain trade-offs between deterministic business logic and LLM-based decision-making.
📌 Genai Engineer Bengaluru
🏢 Cloudray
📍 Bengaluru
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