Ai Ml Engineer

WOW Softech; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

WOW Softech is seeking an experienced AI/ML Engineer to design, develop and deploy enterprise-grade GenAI, RAG and agentic AI solutions for infrastructure and service management.

The ideal candidate will have hands-on expertise in Python, GenAI/LLMs, RAG, AI agents and LangChain/LangGraph, with strong API and cloud/MLOps exposure. In-depth understanding of IT operations, AIOps or Observability is valued.

Qualifications

• Hands-on experience in Python, GenAI/LLMs, RAG and AI agents.
• Experience with LangChain/LangGraph and building GenAI applications.
• Experience with cloud/MLOps and backend API integration.
• Exposure to Infrastructure, IT Operations, AIOps or Observability.

Responsibilities

• Design and develop production-grade GenAI, RAG and Agentic AI applications.
• Build AI copilots/agents for incident analysis, troubleshooting, summarization and operational decision support.
• Develop RAG pipelines using embeddings, vector databases and enterprise knowledge sources.
• Integrate AI solutions with enterprise applications using REST APIs and backend services.
• Work with operational telemetry, monitoring and infrastructure data to support AIOps, anomaly detection and automation.
• Build scalable Python backend services using frameworks such as FastAPI.
• Deploy and monitor AI/ML solutions using cloud and MLOps technologies.

Skills

Python

GenAI/LLMs

RAG

AI Agents

LangChain

LangGraph

APIs

Cloud/MLOps

Infrastructure exposure

IT Operations

AIOps

Observability

Tools

FastAPI

LangChain

LangGraph

REST APIs

Backend services

Job description

Role & responsibilities

We are looking for an experienced AI/ML Engineer to design, develop and deploy enterprise-grade Generative AI, RAG and Agentic AI solutions for Infrastructure and Service Management operations.

The ideal candidate should have strong hands-on experience in Python, GenAI/LLMs, RAG, AI Agents, LangChain/LangGraph, APIs and cloud/MLOps, along with exposure to Infrastructure, IT Operations, AIOps or Observability.

Key Responsibilities

• Design and develop production-grade GenAI, RAG and Agentic AI applications.
• Build AI copilots/agents for incident analysis, troubleshooting, summarization and operational decision support.
• Develop RAG pipelines using embeddings, vector databases and enterprise knowledge sources.
• Integrate AI solutions with enterprise applications using REST APIs and backend services.
• Work with operational telemetry, monitoring and infrastructure data to support AIOps, anomaly detection and automation.
• Build scalable Python backend services using frameworks such as FastAPI.
• Deploy and monitor AI/ML solutions using cloud and MLOps technologies.