Role & 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).

Preferred candidate profile :-

- 58 years of overall software engineering experience, with robust hands-on expertise in Java backend development.




- Proven experience designing and building microservices architectures and enterprise-grade REST APIs.
- Hands-on experience integrating applications with Microsoft SharePoint (bidirectional sync, document/metadata management, permissions) using SharePoint REST/Graph APIs or equivalent.
- Hands-on experience building ServiceNow integrations — REST/SOAP APIs, webhooks, ticket/job synchronization, and workflow automation.
- Working knowledge of AI/LLM-powered services (e.g., Azure OpenAI, Azure AI Foundry) and experience exposing or consuming AI capabilities through APIs.
- Exposure to agentic AI concepts and frameworks (e.g., LangChain, LangGraph, Semantic Kernel) and standardized tool/agent integration protocols such as Model Context Protocol (MCP).
- Solid understanding of RBAC, SSO/authentication (OAuth2/SAML), and audit logging for enterprise integration layers.
- Experience with API gateways, message queues/event-driven integration patterns, and asynchronous processing
- Comfortable working with Git, CI/CD pipelines, containerization (Docker/Kubernetes), and Agile/Scrum delivery practices.
- Strong problem-solving and troubleshooting skills, with the ability to debug complex integration issues across distributed systems.

📌 AI Integration Engineer (Indore)
🏢 kanerika software
📍 Indore