Senior Workforce AI Solutions Engineer at Verisk Analytics in Jersey City, NJ

Job description

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 Authentica