AI Engineer I Hyderabad, Indore & Ahmedabad
AppZime Technologies
Location
🇮🇳 Hyderabad, India
Type
full_time
Salary
Undisclosed
Posted
17h ago
Job Description
AI Engineer Locations We are in Austin (USA), Singapore, Hyderabad, Indore and Ahmedabad (India). Job Location: Hyderabad, Indore and Ahmedabad (India) Experience: 5-8 years
Role Overview
We are looking for an experienced Integration Engineer to design, build, and own the integration layer for an enterprise-grade, agentic AI document platform. The ideal candidate has a strong Java backend and microservices background, deep experience building and consuming REST APIs, and hands-on expertise integrating Microsoft SharePoint and ServiceNow with modern applications. Experience connecting these integrations to AI/LLM-powered services and agentic AI frameworks is highly valued, as
the role
sits at the intersection of enterprise systems integration and the platform's AI agent layer.
Key Responsibilities
Enterprise System Integration • Build and maintain REST APIs and microservices (Java-based) that connect the agentic AI platform to SharePoint, ServiceNow, and other Microsoft ecosystem tools (Word, Excel, PowerPoint, PDF, MS Visio). • Design integration specifications, data contracts, and message/event schemas between the AI agent layer and downstream/upstream enterprise systems. • Support on-prem packaging and third-party add-in compatibility testing as part of deployment readiness. AI/LLM & Agent Integration • Integrate backend microservices with AI/LLM-powered services (Azure OpenAI, Azure AI Foundry). • Implement agent-to-tool and agent-to-system integration patterns, including function/tool calling and standardized protocols such as Model Context Protocol (MCP), in coordination with the AI Engineering team. • Build the plumbing that allows AI agents to trigger, monitor, and act on workflows in SharePoint and ServiceNow (e.g., document routing, approval triggers, status callbacks). • Collaborate with AI Engineers on exposing document parsing, validation, and rules-engine outputs through well-defined APIs consumable by agent orchestration logic (e.g., LangChain / LangGraph).