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 MCP servers and tool integrations extending AI across internal systems
Implement RAG pipelines over lending policies, regulatory docs, and knowledge bases
Develop function-calling and tool-use patterns for safe LLM interaction with databases and APIs
Build evaluation and guardrail frameworks to catch hallucinations and enforce compliance

Engineer the Backend

Architect scalable services using Java, Spring Boot, and Python for production AI features
Design schemas using SQL and NoSQL databases optimized for AI workloads
Build RESTful APIs serving 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
Backend Engineering

Area

Expectation

Languages

Java, Python

Frameworks

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

Databases

SQL (schema design, optimization, indexing) and NoSQL (document, key-value, graph)

APIs & Architecture

RESTful APIs, microservices, domain-driven design, event-driven patterns

Cloud

AWS (Bedrock, SageMaker, Lambda), GCP (Vertex AI), or Azure (OpenAI, Cognitive Services)

DevOps

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

AI / ML Engineering

Area

Expectation

LLM Integration

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

AI Agents & 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

Eval pipelines — accuracy metrics, human-in-the-loop review, regression detection

AI Dev Tools

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.

PayU is an equal opportunity employer.