Agentic AI Engineer

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.
• Strong 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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