Agentic AI Developer

Testunity; India; Remote; INR 1,200,000 - 2,200,000; Full time

Job summary

Testunity is seeking an experienced Agentic AI Developer with strong expertise in Python, LangChain, LangGraph, and LLMs. The candidate will develop intelligent AI agents that can understand tasks, make decisions, use external tools, retrieve relevant information, and execute multi-step workflows with minimal human intervention.

You will build and deploy agents using FastAPI, integrate diverse LLMs, and emphasize robust state management, RAG pipelines, tool calling, and error handling on a

Qualifications

• Hands-on experience building Agentic AI applications with robust state management.
• Experience with LangChain, LangGraph, and LLM integrations is required.
• Strong Python backend development and API integration skills are essential.

Responsibilities

• Develop intelligent AI agents that understand tasks, make decisions, and execute multi-step workflows with minimal human intervention.
• Integrate Python backends with external tools and APIs, ensuring reliability and scalability.
• Design autonomous agent architectures with proper error handling and state management.

Skills

Python

LangChain

LangGraph

LLMs

Agentic AI

Tools

FastAPI

LLM APIs

Job description

Brief JD Overview - Agentic AI Developer

Role: Agentic AI Developer Experience: 6+ years Open Positions: 1 Location: Remote Contract Duration: 3 months Working Time Zone: IST

Role Summary

We are looking for an experienced Agentic AI Developer with strong expertise in Python, LangChain, LangGraph, and Large Language Models (LLMs). The candidate will develop intelligent AI agents that can understand tasks, make decisions, use external tools, retrieve relevant information, and execute multi-step workflows with minimal human intervention.

Key Skills Required

What to Look for While Screening

Prioritize candidates who have hands-on experience building and deploying Agentic AI applications, rather than candidates with only theoretical knowledge of LLMs or prompt engineering.

Ask Candidates About

• Handling failures, loops, state management, and evaluation of AI agents.
• RAG pipelines and retrieval quality.
• Tool calling and function execution.
• Python, FastAPI, and LLM API integrations.
• Multi-agent architecture and agent coordination.
• Projects built using LangGraph or LangChain.
• Agentic AI: Designing autonomous, goal-oriented workflows with appropriate control and error handling.
• FastAPI: Building APIs and backend services for AI applications.
• RAG (Retrieval-Augmented Generation): Connecting LLMs to external knowledge sources for context-aware responses.
• Tool Calling: Enabling AI agents to invoke APIs, functions, and external tools.
• LLM Integration: Integrating models such as GPT, Claude, or other LLMs into applications.
• Multi-Agent Systems: Developing multiple collaborating AI agents to solve complex tasks.
• LangChain & LangGraph: Building LLM-powered applications, agent workflows, and stateful AI systems.
• Python: Strong programming and backend development skills.

Skills: ai agent,llm,python,agents