AI Engineer (Agentic AI | GenAI | LLM)

Vrinda International; India; On-site; INR 1,620,000 - 1,980,000; Full time

Job summary

Vrinda International in India is hiring an AI Engineer (Agentic AI, GenAI, LLMs) for full-time PAN India deployment. Openings: 2; senior consultant up to 18 LPA.

You will design and implement AI agents, integrate LangChain-based pipelines, and collaborate with cross-functional teams. The ideal candidate has strong Python with FastAPI/Flask, NLP expertise, and hands-on cloud experience with Docker/Kubernetes and Azure/AWS/GCP.

Qualifications

• > Hands-on experience in Agentic AI, GenAI, and LLMs.
• > Experience with LangChain, LangGraph, Semantic Kernel, or AutoGen.
• > Strong Python programming skills with FastAPI and Flask.
• > Experience with NLP frameworks such as BERT, SpaCy, NLTK, Word2Vec, or GloVe.
• > Hands-on experience developing AI Agents and multi-agent systems.
• > Experience with Docker, Kubernetes, and cloud platforms (Azure, AWS, or GCP).
• > Experience with SQL, NoSQL, and Vector Databases.
• > Strong understanding of MLOps, prompt engineering, model fine-tuning, and performance optimization.

Skills

GenAI

LLMs

Agentic AI

LangChain

LangGraph

Semantic Kernel

AutoGen

Python

FastAPI

Flask

BERT

SpaCy

NLTK

Word2Vec

GloVe

Multi-agent systems

Docker

Kubernetes

Azure

AWS

GCP

SQL

NoSQL

Vector Databases

MLOps

Prompt engineering

Tools

Docker

Kubernetes

Azure

AWS

GCP

Job description

Job Description

? We're Hiring | AI Engineer (Agentic AI | GenAI | LLM)

? Location: PAN India (As per Business Requirement)

? Employment Type: Full-Time

? Openings: 2

Compensation

? Senior Consultant (5–8 Years): Up to ₹18 LPA

Requirements

Required Skills

• Strong hands-on experience in Agentic AI, GenAI, and LLMs.
• Experience with LangChain, LangGraph, Semantic Kernel, or AutoGen.
• Strong Python programming skills with FastAPI and Flask.
• Experience with NLP frameworks such as BERT, SpaCy, NLTK, Word2Vec, or GloVe.
• Hands-on experience developing AI Agents and multi-agent systems.
• Experience with Docker, Kubernetes, and cloud platforms (Azure, AWS, or GCP).
• Experience with SQL, NoSQL, and Vector Databases.
• Strong understanding of MLOps, prompt engineering, model fine-tuning, and performance optimization.