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.

Purpose of the Role

• Accelerate measurable business value from enterprise workforce AI investments.
• Design and deliver AI-powered solutions that improve productivity, reduce manual effort, and simplify business processes.
• Act as a technical advisor and solution architect for workforce AI technologies.
• Establish reusable agents, skills, integrations, MCP components, and solution patterns that can be leveraged across the organization.
• Drive responsible AI adoption while meeting enterprise security, governance, privacy, and compliance requirements.

Key Responsibilities

Request Queue Management and Solution Delivery

• Lead and coordinate delivery activities with the coworker supporting each request, including work allocation, technical direction, issue resolution, and completion accountability.
• Manage and prioritize a queue of qualified AI solution requests received from business units across the company.
• Partner with the intake and triage function to confirm scope, readiness, ownership, dependencies, and the appropriate delivery path, then lead execution with the coworker assigned to support delivery.
• Work directly with requesters to understand business processes, desired outcomes, data needs, risks, and success measures.
• Translate business requirements into practical AI solutions using approved platforms and technologies.
• Estimate effort, communicate delivery expectations, document decisions, and maintain visibility into request status and outcomes.
• Provide appropriate implementation documentation, knowledge transfer, and transition to an ongoing support model.

AI Solution Architecture and Engineering

• Design AI-enabled workflows, agents, automations, and business process improvements.
• Select the appropriate platform and implementation approach based on business needs, technical fit, security, maintainability, and cost.
• Build solutions through simple builder experiences, low-code platforms, and pro-code development using Visual Studio or Visual Studio Code when needed.
• Create reusable design patterns, templates, components, and engineering standards that improve delivery speed and consistency.
• Evaluate scalability, observability, supportability, and lifecycle requirements before production use.

Agent, Skill, and MCP Development

• Build and maintain purpose-specific AI agents, actions, prompts, workflows, and orchestration logic.
• Develop custom skills and Model Context Protocol (MCP) servers or integrations when platform-native capabilities are insufficient.
• Extend AI platforms using APIs, SDKs, custom connectors, functions, and other approved integration methods.
• Apply software development practices such as source control, testing, documentation, release management, and reusable code design.

Integration, Data, and Authentication

• Design secure connections between workforce AI platforms and enterprise data sources, knowledge repositories, business applications, and external functions.
• Understand and apply modern authentication and authorization patterns, including OAuth, Microsoft Entra ID, application registrations, service principals, managed identities, delegated access, and API-based credentials.
• Partner with application owner…