Job Title: Python + Agentic AI Engineer

Experience: 4–8 Years

Location: Pune / Hyderabad / Chennai / Bangalore

Work Mode: Hybrid

Job Summary

We are looking for an experienced Agentic AI Engineer with 4–8 years of software development experience and strong hands-on expertise in Python, Generative AI, LLMs, RAG, and Agentic AI systems .

The ideal candidate should have experience designing and developing AI agents, agentic workflows, LLM-powered applications, and enterprise AI solutions using technologies such as LangChain, LangGraph, Vector Databases, APIs, Azure, and CI/CD .

The candidate will be responsible for building scalable and production-ready Agentic AI solutions that can reason, use tools, retrieve information, execute tasks, and interact with enterprise systems.

Mandatory Technical Skills-

Programming

- Strong hands-on experience with Python .
- Strong understanding of Object-Oriented Programming .
- Experience in Python-based application and API development .
- Strong problem-solving and debugging skills.

Generative AI & LLMs

- Hands-on experience working on Generative AI projects .
- Strong understanding of Large Language Models (LLMs) .
- Experience with LLM integration and API-based AI solutions .
- Hands-on experience with Retrieval-Augmented Generation (RAG) .
- Strong understanding of Prompt Engineering .
- Hands-on experience developing Agentic AI applications and workflows .

Agentic AI

- Experience designing and developing AI Agents capable of executing multi-step tasks.
- Understanding of agent orchestration and workflow automation .
- Experience with tool/function calling and integrating external tools or enterprise APIs.
- Experience building multi-step and stateful agent workflows .
- Understanding of agent memory, context management, and decision-making workflows .
- Experience with multi-agent systems is preferred.
- Ability to integrate LLMs with enterprise applications and business processes.

GenAI Frameworks

- Strong hands-on experience with LangChain .
- Strong hands-on experience with LangGraph .
- Experience building agentic workflows using LangChain/LangGraph .
- Understanding of agent orchestration, tools, nodes, states, and workflows.

RAG & Vector Databases





- Hands-on experience building RAG pipelines .
- Experience with Vector Databases .
- Understanding of Embeddings and Semantic Search .
- Experience implementing vector-based information retrieval.
- Ability to optimize retrieval pipelines for relevance and performance.

Cloud & DevOps

- Hands-on experience with Microsoft Azure .
- Experience developing and integrating REST APIs .
- Understanding of microservices architecture .
- Experience with CI/CD pipelines .
- Experience deploying and managing AI applications in cloud environments.
- Understanding of production deployment, monitoring, scalability, and reliability.

Databases

- Strong understanding of SQL .
- Experience working with databases for AI application development and data retrieval.
- Understanding of data integration with RAG and Agentic AI applications.

Key Responsibilities

- Design, develop, and deploy Agentic AI applications using Python.
- Build intelligent AI agents capable of reasoning, tool usage, information retrieval, and task execution .
- Design and implement agentic workflows using LangChain and LangGraph.
- Develop RAG-based Agentic AI solutions for enterprise use cases.
- Integrate LLMs into enterprise applications and business processes.
- Develop AI agents that interact with APIs, databases, tools, and external systems .
- Implement effective Prompt Engineering strategies to improve agent performance.
- Design and implement Vector Database solutions for semantic search and knowledge retrieval.
- Build scalable microservices and REST APIs for AI-powered applications.
- Develop and integrate tool/function-calling capabilities for AI agents.
- Implement agent memory, state management, context handling, and workflow orchestration .
- Deploy and manage Agentic AI solutions on Microsoft Azure .




- Implement CI/CD pipelines for application deployment.
- Optimize LLM, RAG, and agent workflows for performance, scalability, reliability, and cost efficiency .
- Troubleshoot and resolve issues related to LLM integrations, RAG pipelines, APIs, and agent workflows.
- Collaborate with architects, developers, data scientists, and business stakeholders to design and deliver enterprise AI solutions.
- Ensure Agentic AI applications are secure, scalable, reliable, and production-ready .

Required Experience

- 4–8 years of overall software development experience.
- Solid hands-on experience in Python development .
- Proven experience delivering Generative AI / LLM-based applications .
- Hands-on experience developing Agentic AI solutions or AI agents .
- Strong experience with RAG and LLM integration .
- Hands-on experience with LangChain and LangGraph .
- Experience with Vector Databases, embeddings, and semantic search .
- Experience developing REST APIs and microservices .
- Experience with Azure and CI/CD .
- Strong understanding of SQL and database integration .
- Ability to clearly explain AI architecture, agent workflows, technical implementation, and individual contributions.

Preferred Candidate Profile

- Strong understanding of Agentic AI architecture and LLM-based application development .
- Experience with multi-agent systems and agent orchestration .
- Good understanding of AI agent planning, tool use, memory, state management, and workflow execution .
- Strong programming and analytical skills.
- Ability to design scalable and production-ready AI solutions.
- Ability to independently troubleshoot and optimize AI applications.
- Comfortable working as an Individual Contributor and taking ownership of assigned tasks.
- Ability to clearly explain previous projects, architecture, implementation approach, and personal technical contributions.

Core Technology Stack

- Python | Generative AI | LLMs | Agentic AI | AI Agents | RAG | Lang Chain | Lang Graph | Vector Databases | Embeddings | Semantic Search | Prompt Engineering | Tool Calling | REST APIs | Microservices | Azure | CI/CD | SQL

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