Role Overview

We are looking for a skilled Python Full Stack / Agentic AI Engineer to design, develop, and deploy AI-powered applications and intelligent agentic workflows. The ideal candidate should have strong expertise in Python, FastAPI, LLMs, RAG, LangChain/LangGraph, and modern full-stack development.

You will work on building scalable backend services, integrating Large Language Models, developing AI agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and creating production-ready AI applications.

Key Responsibilities

- Design and develop scalable backend applications using Python and FastAPI.
- Build and deploy Agentic AI solutions using LLMs and agent frameworks.
- Develop multi-step and multi-agent workflows using LangChain and LangGraph.
- Design and implement RAG (Retrieval-Augmented Generation) pipelines.
- Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
- Develop prompt engineering strategies and structured LLM workflows.
- Work with vector databases and embedding models for semantic search and knowledge retrieval.
- Build APIs and microservices for AI-powered applications.
- Integrate AI services with databases, third-party APIs, and enterprise systems.
- Develop conversation memory, tool calling, function calling, and agent orchestration capabilities.
- Implement evaluation, monitoring, logging, guardrails, and error handling for AI applications.
- Optimize applications for performance, scalability, reliability, and cost.
- Collaborate with product managers, frontend developers, data engineers, and other stakeholders.
- Write clean, maintainable,



well-tested, and production-ready code.
- Participate in architecture discussions, code reviews, testing, and deployment activities.

Required Skills

Programming & Backend

- Solid proficiency in Python.
- Hands-on experience with FastAPI, REST APIs, and backend development.
- Strong understanding of asynchronous programming, API design, authentication, and middleware.
- Experience with SQL/NoSQL databases.

Generative AI / Agentic AI

- Robust understanding of LLMs and Generative AI.
- Hands-on experience building AI Agents / Agentic AI applications.
- Experience with LangChain and/or LangGraph.
- Knowledge of agent orchestration, tool calling, function calling, memory, and workflow management.
- Strong understanding of prompt engineering.

RAG

- Experience designing and implementing RAG architectures.
- Knowledge of document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
- Experience with vector databases such as FAISS, Chroma, Pinecone, Weaviate, Qdrant, or similar.

LLM & AI Integration

- Experience integrating commercial or open-source LLMs.
- Understanding of embeddings, context windows, temperature, token usage, and model selection.
- Experience with structured outputs and LLM-based workflows.
- Familiarity with LLM evaluation and observability is a plus.

Full Stack

- Working knowledge of HTML, CSS, JavaScript/TypeScript.
- Experience with React.js or similar frontend frameworks is preferred.
- Ability to integrate frontend applications with Python/FastAPI services.

Skills:- Python, Agentic AI and LangChain

📌 Python, Gen AI (Bengaluru)
🏢 VY SYSTEMS PRIVATE
📍 Bengaluru