AI Engineer

Wibmo Inc.; Bengaluru; Hybrid; INR 2,800,000 - 4,000,000; Full time

Job summary

PayU Finance India is seeking an AI Engineer to ship production AI systems and back-end services, delivering autonomous agents and intelligent integrations that influence lending decisions.

You will own the full lifecycle—from evaluating new LLM capabilities to deploying agents handling real traffic with real financial consequences. Hands-on production experience is required.

Qualifications

• Hands-on experience deploying AI-powered systems in production.
• Experience building AI-backed backend services and LLM integrations.
• Experience with RAG pipelines, memory, and tool-use patterns.

Responsibilities

• Deploy AI agents for lending workflows - document verification, bureau analysis, risk assessment, customer communication
• Build MCP servers and tool integrations across internal systems
• Implement RAG pipelines over policies, regulatory docs, and knowledge bases
• Develop function-calling and tool-use patterns for safe LLM interaction with databases and APIs
• Review AI-generated code for correctness, security, and project standards; build guardrails and eval frameworks

Skills

Java

Python

LLM Integration

AI Agents

MCP

RAG & Vectors

Prompt Engineering

Evaluation & Guardrails

Security & Compliance

SQL/NoSQL

Education

Bachelor's / Master's in CS/AI/Data Science/Mathematics

Tools

Spring Boot

Spring Data JPA

Spring Security

FastAPI

Flask

Git

Maven/Gradle

Docker

CI/CD

Job description

AI Engineer
Company:PayU Finance India | Experience:4-7 years | Location:India - Hybrid (Gurugram / Bangalore)

| Type:Full-time, IC`

About the Role

We need an AI Engineer who ships production AI systems — not prototypes. You'll build AI-powered backend services, autonomous agents, and intelligent integrations that directly impact lending decisions and operational e ciency.

You own the full lifecycle — from evaluating a new LLM capability to deploying an agent that handles real tra c with real financial consequences.

Prior hands-on experience building and deploying AI-powered systems in production is a must.

What You'll Do

Build AI Systems

• Deploy AI agents for lending workflows - document verification, bureau analysis, risk assessment, customer communication
• Build MCPserversand tool integrations extending AI across internal systems
• Implement RAGpipelinesover lending policies, regulatory docs, and knowledge bases
• Develop function-callingandtool-usepatterns for safe LLM interaction with databases and APIs
• Build evaluationandguardrailframeworksto catch hallucinations and enforce compliance

Engineer the Backend

• Architect scalable services using Java,SpringBoot,andPythonfor production AI features
• Design schemas using SQLandNoSQLdatabasesoptimized for AI workloads
• Build RESTfulAPIsserving model inference at low latency and high throughput
• Integrate with credit bureaus, banking partners, and payment gateways Raise the Bar

Code reviews for AI patterns and security, optimize token costs and latency, establish AI observability, and drive AI-assisted development (Cursor, Copilot) across the team.

Review and validate AI-generated code for correctness, security, and project standards. Build test suites, guardrails, and eval frameworks for prompts and agent behaviors - with continuous benchmarks, drift detection, and human-in-the-loop review before production.

Required Skills

Area

Languages

Java, Python

Frameworks

Spring Boot, Spring Data JPA, Spring Security; FastAPI or Flask

Databases

Cloud

DevOps

Git, Maven/Gradle, Docker, CI/CD pipelines

Area

LLM Integration

Claude, GPT-4, Gemini - API usage, structured output, context management

AIAgents&MCP

Built agents with planning, tool-use, memory; developed MCP servers and tools

RAG & Vectors

Retrieval-augmented generation - chunking, embedding, reranking, vector search

Prompt Engineering

System prompts, few-shot, chain-of-thought, function calling, output parsing

Evaluation

AIDevTools

Daily use of Cursor AI, GitHub Copilot, or equivalent

Education

Bachelor's / Master's in CS, AI/ML, Data Science, or Mathematics - or equivalent hands-on experience. We value what you've built over where you studied.