- Agentic AI
- Has built and deployed AI agents, not just chatbots, agents that call tools/APIs and complete multi-step tasks
- Hands-on with agent frameworks: LangGraph, LangChain, Semantic Kernel, AutoGen or CrewAI
- Tool/function calling, MCP (Model Context Protocol), multi-agent workflows
- Human-in-the-loop: agent pauses for human approval before risky actions
- Agent state and memory (e.g. Redis, Postgres), guardrails for safety
- Generative AI
- 2.5–3+ years hands-on GenAI work (not just general AI/ML)
- LLM APIs: Azure OpenAI / OpenAI
- RAG, embeddings, vector databases (Azure AI Search, pgvector, Pinecone, FAISS)
- Prompt engineering and structured outputs
- Engineering and production
- Robust Python, FastAPI, Docker, Kubernetes/AKS, CI/CD
- Testing and evaluation of AI outputs (golden test sets, Ragas, DeepEval, LLM-as-judge)
- Monitoring and observability (OpenTelemetry, LangSmith, Langfuse, App Insights/Dynatrace)
- Cost, reliability and PII/security handling
- Platform mindset
- Built reusable components, templates, SDKs or frameworks used by multiple teams

📌 AI Engineer (Bengaluru)
🏢 LTM
📍 Bengaluru