AI Engineer

WillWare Technologies; Bengaluru; Hybrid; INR 1,200,000 - 2,800,000; Full time

Job summary

Willware Technologies in Bengaluru is seeking an AI Engineer specializing in GenAI and multi-agent systems. The role requires 4-9 years of experience and offers a hybrid work model with 4 days WFO.

The position operates on a shift from 1:00 PM to 10:00 PM, and Willware emphasizes hands-on development of AI agents and enterprise AI solutions. The candidate will work with LangChain, RAG, and cloud AI platforms (Azure/AWS/GCP), building AI copilots and integrating with vector databases and MLOps

Qualifications

• Experience with GenAI and multi-agent systems.
• Proficiency in Python and AI tooling.
• Hands-on experience with LLMs, RAG, and vector databases.

Skills

Python

Generative AI

Large Language Models

Agentic AI

LangChain

CrewAI

AutoGen

Semantic Kernel

OpenAI

Azure OpenAI

Claude

Llama

RAG

Vector Databases

Prompt Engineering

AI Agent Development

Docker

Kubernetes

CI/CD

Azure

Job description

Position: AI Engineer - GenAI & Multi-Agent Systems

Experience: 4-9 Years

Location: Bangalore

Work Mode: Hybrid (4 Days WFO)

Shift: 1:00 PM - 10:00 PM

Company: Willware Technologies

Exp: 4- 9 years

Location: Bangalore

Work Mode: 4 Days Office

Position: AI Engineer - GenAI & Multi-Agent Systems

Experience: 4-9 Years

Location: Bangalore

Work Mode: Hybrid (4 Days WFO)

Shift: 1:00 PM - 10:00 PM

Key Skills Required:

• Python
• Generative AI (GenAI)
• Large Language Models (LLMs)
• Agentic AI / Multi-Agent Systems
• LangChain, CrewAI, AutoGen, Semantic Kernel
• OpenAI / Azure OpenAI / Claude / Llama
• RAG (Retrieval-Augmented Generation)
• Vector Databases (FAISS, Pinecone, Weaviate)
• Prompt Engineering & AI Agent Development
• Docker, Kubernetes, CI/CD
• Azure (Preferred) / AWS / GCP

Preferred Experience:

• Building AI Agents, AI Copilots, and Autonomous Assistants
• API integrations and enterprise AI solutions
• LLMOps / MLOps exposure
• Knowledge Graphs, RAG evaluation, or Agent Planning frameworks