Job Description:

Design and architect enterprise-grade Agentic AI and Generative AI solutions using LLMs.

Build multi-agent and autonomous AI workflows using frameworks such as LangGraph / LangChain.

Design and implement advanced RAG (Retrieval-Augmented Generation) architectures.

Develop LLM-powered applications including AI agents, copilots, conversational AI, and intelligent automation solutions.

Evaluate and integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, Llama and other foundation models.

Design agent orchestration, tool calling, memory, planning, routing, reflection and human-in-the-loop workflows.

Architect vector search and knowledge retrieval solutions using technologies such as FAISS, Pinecone, Azure AI Search, OpenSearch, Weaviate or similar.

Develop document ingestion,



chunking, embedding, retrieval, reranking and context-management pipelines.

Define scalable architecture patterns for LLM applications and AI agents.

Implement LLM evaluation, observability, guardrails, prompt management and performance optimization.

Work closely with engineering, product, data and business teams to convert business requirements into AI solutions.

Mentor engineers and provide technical leadership for AI/ML and GenAI initiatives.

Drive PoCs from concept to production and establish engineering best practices for enterprise GenAI adoption.

📌 Microsoft Purview Data Governance Engineer (India)
🏢 Acme Services
📍 India