Lead Data Analyst

Job Description

• Skill Set :

  Agentic AI Development

• Total Experience :

  7.00 to 10.00 Years

• No of Openings :

  1

• Job Post Date :

  28/10/2026

• Job Expiry Date :

  30/11/2026

• Domain :

  IT

• Location :

  PUNE [India]

• Job Reference No :

  4115310

Job Summary

Agentic AI Developer

Mandatory Skill - Python , LangGraph , LangChain , RAG , knowledge in containerize and deploy AI services using Docker, Kubernetes, CI/CD pipelines

Location - Pune , Hyderabad , Bangalore , Noida

Shift Timings-Secondshift till 11 pm IST

Role Summary

We are looking for an Agentic AI Developer to design, develop, and deploy intelligent AI agents capable of reasoning, planning, using enterprise tools and APIs, maintaining contextual memory, and autonomously executing multi-step workflows.

The ideal candidate will have strong software engineering skills combined with hands-on experience in Large Language Models, Retrieval-Augmented Generation (RAG), agent orchestration, APIs, vector databases, and cloud AI platforms.

The role will involve transforming business processes into secure, reliable, observable, and scalable agentic AI solutions.

Key Responsibilities

• Design and develop Agentic AI applications capable of autonomous planning, reasoning, tool usage, and multi-step task execution.
• Build single-agent and multi-agent architectures for enterprise use cases.
• Develop AI workflows using frameworks such as LangGraph, LangChain or equivalent agent frameworks.
• Integrate LLMs with enterprise applications, databases, APIs, search platforms, and business workflows.
• Build RAG pipelines for grounding LLM responses using structured and unstructured enterprise knowledge.
• Develop and integrate REST APIs and microservices using Python and frameworks such as FastAPI.
• Design appropriate short-term and long-term agent memory strategies.
• Implement AI agent evaluation across accuracy, task completion, latency, token consumption, and cost.
• Optimize LLM applications for performance, reliability, scalability, and cost.
• Containerize and deploy AI services using Docker, Kubernetes, CI/CD pipelines, and cloud-native services.
• Collaborate with architects, data scientists, product owners, business analysts, security teams, and application developers.
• Conduct technical PoCs and convert successful experiments into production-ready enterprise solutions.
• Maintain technical documentation covering agent architecture, prompts, workflows, APIs, data flows, security controls, and operational procedures.

Required Technical Skills

Core Development

• Strong programming skills in Python
• REST API development using FastAPI / Flask
• Git and modern software engineering practices
• Microservices and asynchronous programming concepts
• SQL and NoSQL databases

Agentic AI

• Large Language Models and Generative AI
• Prompt engineering and prompt management
• RAG
• Embeddings and semantic search
• Function/tool calling
• Structured outputs
• Agent planning and orchestration
• Context and memory management
• Multi-agent systems
• Human-in-the-loop workflows

Agent Frameworks

Hands-on experience with of:

• LangGraph / LangChain

pply.