AI Engineer Job Details | PayU Payments

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. Apply now » Find similar jobs: . Copyright 2025 PayU. All rights reserved / Privacy / Terms of use × Cookie Consent Manager When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer. Required Cookies These cookies are required to use this website and can't be turned off. Required Cookies Show More Details Required Cookies Provider

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