AI Systems Engineer

AI Systems Engineer Who We Are: Founded in 1994, Integrated Medical Systems, Inc. (IMS) is one of the nation's leading distributors serving the alternate-site healthcare market. We build valued partnerships with our customers by providing flexible rental and purchase options for a broad portfolio of disposable and rental products supporting infusion, respiratory, enteral feeding, oncology, and cleanroom applications. At IMS, our people are innovative, dedicated, and experienced, working together to deliver an exceptional customer experience from start to finish. When you join IMS, you'll have the opportunity to work alongside industry experts and thought leaders at a company committed to employee growth, innovation, and well-being. About the Role IMS is seeking an AI Systems Engineer to design, build, and deploy intelligent, agentic AI applications that connect with enterprise data, business systems, and external services. This is an AI application engineering role, not a traditional machine learning or model-training position. You'll focus on building the systems that allow AI models to work with real-world data and business tools—creating secure, reliable, and scalable AI agents that can understand context, access information, use tools, and take action. You'll work heavily with Model Context Protocol (MCP), LLM orchestration, APIs, tool calling, enterprise data, and asynchronous application architectures to turn individual AI models into capable business applications. What You Bring to the Table Required Qualifications Programming & Software Architecture • Strong proficiency in Python or TypeScript. • Strong understanding of asynchronous programming and async/await patterns. • Experience building and consuming RESTful APIs. • Understanding of JSON-RPC 2.0 and message-based communication.AI & MCP • Hands-on experience building Model Context Protocol (MCP) servers using standard SDKs or frameworks such as FastMCP. • Experience working with MCP tools, resources, and prompts. • Strong understanding of LLM APIs and tool/function calling. • Experience integrating leading LLM platforms such as OpenAI, Anthropic Claude, or comparable services.Data & Search • Experience working with vector databases/vector stores and AI-powered retrieval. • Ability to build search and retrieval tools that provide relevant, structured context to LLMs. • Understanding of document identifiers, metadata, and citation/source handling.Security • Understanding of secure authentication and authorization practices for connecting AI applications to proprietary data and enterprise systems. • Ability to design appropriately scoped access between AI agents, internal systems, and external services. Preferred Qualifications • Experience developing agentic AI applications or multi-step AI workflows. • Experience with FastMCP or other MCP frameworks. • Experience with LangChain, LangGraph, Semantic Kernel, or similar AI orchestration frameworks. • Experience with Docker, Git, CI/CD, and cloud platforms. • Experience integrating AI with enterprise databases, ERP systems, CRM platforms, or other business applications. • Experience with observability, logging, testing, and monitoring of AI applications. • Familiarity with healthcare data, privacy, security, or compliance requirements. What Success Looks Like In this role, you'll help IMS move AI from experimentation into practical, secure, business-ready applications. Success means building AI systems that can: • Understand the right context • Find and retrieve the right information • Use the appropriate business tools • Interact securely with enterprise systems • Choose the right model for the task • Execute workflows reliably • Provide accurate, traceable responsesYou'll be helping build the infrastructure and application layer that makes AI useful within the business. What You'll Do Build AI & MCP Applications • Design, develop, and deploy Model Context Protocol (MCP) servers that securely connect AI applications to internal databases, vector stores, business applications, and other enterprise resources. • Build standardized interfaces that allow AI agents to discover and interact with available tools, resources, and workflows. • Develop MCP tools, resources, and prompts to support repeatable business workflows.Orchestrate Large Language Models • Evaluate and select the appropriate LLM for specific use cases based on reasoning capabilities, cost, context window, latency, and performance. • Design AI workflows that strategically route tasks across multiple models and services. • Implement tool calling and function calling to enable AI agents to interact with external systems.Integrate APIs & Business Systems • Build reliable REST API and third-party system integrations. • Configure function calling and tool schemas that allow AI agents to invoke external services. • Transform external system responses into structured formats that can be effectively interpreted and used by LLMs. • De