Generative AI Engineer

Years of experience - 4 to 12 Years

Location -South Delhi

Role Overview:

You will be responsible for the hands-on development, coding, and deployment of AI-powered features. Your focus is on writing clean, productive code to integrate LLMs into our existing tech stack, building robust data pipelines for RAG, and ensuring the reliability of model outputs through rigorous testing and optimization.

Key Responsibilities

- Application Implementation: Code and integrate LLM APIs (OpenAI, Anthropic, etc.) or local models into backend services using Python, FastAPI, etc.,
- MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript) to expose internal databases, APIs, and file systems to AI agents.
- RAG Implementation: Build and maintain the "plumbing" for Retrieval-Augmented Generation-specifically coding the data ingestion scripts, text chunking logic, and metadata filtering.
- Vector DB Management:



Perform day-to-day operations on vector databases (Pinecone, Milvus, etc.), including indexing, querying, and optimizing search retrieval.
- Prompt Programming: Develop, version-control, and refine complex prompt templates (using Jinja2 or similar) to ensure consistent structured outputs (JSON/YAML).
- Agent Development: Implement multi-step workflows using LangChain, LangGraph, CrewAI etc.,, focusing on tool-calling logic and error handling.

Technical Skills (The "Execution" Stack)

- Monitor AI systems for performance, hallucinations, and overall user experience.
- Hands-on experience with Generative AI and LLM applications
- Experience building RAG pipelines
- Knowledge of embeddings and semantic search
- Familiarity with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar frameworks.
- Experience with AI agents and workflow orchestration

📌 Generative AI Engineer (New Delhi)
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