Generative AI/Agentic AI Engineer - Python/LangChain
First seen by Alion on Sep 18, 2026.
Generative AI / Agentic AI Engineer
Experience : 2+ Years
Employment Type : Full-time
Position Overview :
We are building next-generation Agentic AI systems designed for real-world production deployment - moving beyond proof-of-concepts (POCs) to scale complex multi-agent architectures, advanced RAG pipelines, and enterprise LLMOps.
Key Responsibilities :
- RAG & Knowledge Retrieval : Design and deploy end-to-end RAG pipelines (ingestion, chunking, embeddings, hybrid retrieval, reranking) and Graph RAG / Knowledge Graph-based retrieval systems.
- Multi-Agent Workflows : Architect scalable multi-agent systems featuring tool/API integration, persistent memory, guardrails, and human-in-the-loop governance.
- Optimization & Performance : Drive latency, cost, and scale optimizations through semantic caching, model routing, and token usage optimization.
- Observability & Evaluation : Build robust tracing, evaluation, and monitoring frameworks for LLMs and agentic workflows.
Required Qualifications & Skills :
- Experience : 2+ years of hands-on experience building GenAI/LLM applications and taking them from POC to production.
- Core Tech Stack : High proficiency in Python and frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or AutoGen.
- APIs & Vector DBs : Experience with Vector Databases and LLM integrations (OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models).
- Production Operations : Solid grasp of hallucination reduction techniques, system guardrails, observability tools, and cost tuning.
Preferred Qualifications : Educational background from premier engineering institutes (IIT, IISc, BITS, or NIT).
Skills
Python, LangChain, LLMOps, LangGraph, Knowledge Graph, Agentic AI, Generative AI, VectorDB