Application Engineer | AI Automation, MCP and RAG

This is a flash storage company reshaping enterprise data storage, and the role sits on the internal automation side rather than in the storage product itself. The work is genuinely current: architecting MCP servers that expose business systems to AI agents, decomposing the data models of enterprise applications to build usable schemas for those agents, and building retrieval augmented generation pipelines and agents that complete real tasks with minimal human input. Stack is Python for the AI orchestration plus TypeScript or Java for the enterprise services, with deep REST API and OAuth work throughout. Be clear eyed about one thing: the systems being automated are Salesforce, Zuora and ServiceNow. It is modern AI engineering pointed at back office platforms.

Stated requirement is 5+ years in professional software engineering. Skills as published: expert level Python for AI and ML orchestration, plus JavaScript or TypeScript or Java for the enterprise services layer; working knowledge of Salesforce Sales Cloud, where understanding the API and object model is mandatory and Apex is a bonus rather than a requirement; proven experience building AI agents with MCP (Model Context Protocol) and implementing RAG architectures; and deep expertise designing and consuming RESTful APIs including complex authentication and OAuth flows. Responsibilities: design and implement MCP servers that expose services such as Quote, Opportunity and Renewal to AI agents; rapidly decompose the data models of enterprise applications including Zuora, Salesforce and ServiceNow into schemas that AI can work with; and build and optimise RAG workflows and agents that execute multi step tasks with minimal supervision. Honest fit guidance, because the title undersells and the domain oversells in opposite directions. The technology is genuinely modern, MCP and RAG work in production is still rare, and five years is a reasonable bar for it. But the systems you are automating are the company's own commercial back office, so the users are internal sales and finance operations rather than external customers, and success is measured in process time saved rather than product shipped. If you want AI engineering experience on your CV and do not mind that the domain is quote to cash, this is a strong opportunity. If you want to build the storage product, this is not that team. Location is Bangalore.