Senior Workforce AI Solutions Engineer

Join Verisk's Workforce Technology Services organization as a Workforce AI Solutions Engineer. This role partners directly with business stakeholders across the enterprise to identify, design, build, and deploy AI-powered solutions using approved workforce AI platforms, including Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, and associated technologies. The position serves as the technical lead and primary owner for a queue of business-submitted AI solution requests that require light-to-moderate implementation effort. The person in this role leads each engagement while remaining directly involved in solution design, development, testing, and delivery alongside a collaborating coworker. Requests may include workflow automation, AI agent development, system integrations, document intelligence, knowledge retrieval, process simplification, and productivity optimization. The role works with a partner team responsible for initial intake and triage so that simple questions, training needs, and requests requiring clarification are handled separately. This position receives qualified requests that need hands-on technical design and delivery but do not require a large-scale software development engagement. Required Qualifications Experience in solution architecture, software engineering, automation, cloud engineering, application integration, or a related technology discipline. Demonstrated experience delivering business-facing technical solutions from requirements through implementation. Hands-on experience with one or more enterprise AI platforms such as Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, or comparable technologies. Experience working with APIs, SDKs, integrations, automation technologies, and structured or unstructured enterprise data sources. Working knowledge of enterprise identity, authentication, authorization, and secure integration patterns. Ability to build through both low-code and pro-code approaches and to select the appropriate method for the request. Strong analytical, consulting, documentation, troubleshooting, and stakeholder communication skills. Ability to manage multiple requests, balance business urgency with technical risk, and drive work to completion. Preferred Qualifications Experience building custom agents, AI assistants, agent actions, and multi-step AI workflows. Experience developing MCP servers, custom skills, plugins, connectors, or similar extensibility components. Experience with Microsoft Graph, REST APIs, Azure Functions, Logic Apps, Power Automate, GitHub, Visual Studio, or Visual Studio Code. Knowledge of retrieval-augmented generation, enterprise search, grounding, vector search, and knowledge-management patterns. Knowledge of responsible AI, data protection, security, compliance, auditability, and AI governance practices. Experience identifying and measuring productivity, process, service-quality, or business-value improvements. Success Measures Timely movement of qualified requests from intake through delivery or an agreed disposition. Business requester satisfaction and adoption of delivered solutions. Demonstrated productivity, quality, service, or process improvements from implemented solutions. Creation and reuse of standard agents, skills, MCP components, connectors, and solution patterns. Reliable, secure, supportable solutions that comply with enterprise governance and architecture requirements. Clear documentation, ownership, and lifecycle management for solutions placed into use. Candidate Profile The successful candidate combines curiosity about emerging AI capabilities with disciplined enterprise engineering. They can move comfortably between a business process conversation and a technical design discussion, explain tradeoffs clearly, build practical solutions, and recognize when a request should be simplified, escalated, or redirected. They are accountable for outcomes, thoughtful about risk, and motivated by improving how employees work. #LI-LM03 #LI-Remote