Agentic AI and Gen AI Developer

Actively Reviewing

Neev

Gurugram Full-Time 4–8 yrs exp Posted 5 hours ago · Apply by Sep 16, 2026

Job Description

Job Description – Agentic AI & Generative AI Developer

Job Title: Agentic AI & Generative AI Developer

Experience: 7–15 Years

Employment Type: Full-Time

Job Summary

We are looking for an experienced Agentic AI & Generative AI Developer to design, develop, and deploy production-grade AI applications powered by Large Language Models (LLMs) and autonomous AI agents. The ideal candidate should have strong expertise in Python, Agentic AI frameworks, RAG architecture, LLM orchestration, cloud-native deployment, and AI platform engineering.

This role offers an opportunity to work on next-generation AI platforms supporting enterprise and telecom transformation projects by building intelligent AI assistants, multi-agent systems, and autonomous workflow automation solutions.

Key Responsibilities Agentic AI Development

Design and develop autonomous AI agents capable of reasoning, planning, and executing complex workflows.
Build multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen, and similar frameworks.
Implement Agent-to-Agent (A2A) collaboration, memory management, and tool integration.
Develop AI agents capable of integrating with enterprise APIs, databases, and business applications.

Generative AI Development

Build enterprise applications using Large Language Models (GPT, Claude, Llama, Gemini, etc.).
Develop Retrieval Augmented Generation (RAG) pipelines using embeddings and vector databases.
Implement prompt engineering, function calling, tool usage, and fine-tuning strategies.
Develop conversational AI solutions, AI Assistants, and enterprise Copilots.

AI Platform Engineering

Design scalable AI architectures using microservices and cloud-native technologies.
Integrate AI applications with APIs, enterprise platforms, and cloud services.
Build end-to-end AI pipelines from data ingestion to deployment.
Optimize inference performance, scalability, observability, and monitoring.

Cloud & DevOps

Deploy AI applications on AWS, Azure, or GCP.
Work with Docker, Kubernetes, EKS, ECR, and CI/CD pipelines.
Implement MLOps best practices and model lifecycle management.

AI Governance

Design evaluation frameworks for LLM performance.
Implement AI safety, guardrails, monitoring, and governance.
Debug, optimize, and continuously improve AI agent performance.

Required Skills Mandatory Skills

Python Programming
Generative AI
Large Language Models (LLMs)
Agentic AI
LangChain
LangGraph
CrewAI
AutoGen
Model Context Protocol (MCP)
Retrieval Augmented Generation (RAG)
Prompt Engineering
Embeddings
Vector Databases
API Integration
Microservices

Good to Have

Pinecone
ChromaDB
Qdrant
Weaviate
Neo4j
Knowledge Graphs
Graph Databases
Machine Learning
Deep Learning
NLP
Transformer Models
Docker
Kubernetes
AWS
Azure
GCP
MLOps
CI/CD
Reinforcement Learning

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related discipline.
7–15 years of software development experience with at least 3 years in Generative AI.
Experience developing production-grade AI applications.
Experience with cloud-native AI deployments.
Excellent problem-solving and communication skills.
Ability to work in a fast-paced product engineering environment.

Skills: llm,gen,python,agnetic,ai,developer