Senior Workforce AI Solutions Engineer

Verisk • Jersey City, NJ

10h • Remote

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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 owners, data owners, security, privacy, architecture, and identity teams to establish approved access patterns.
• Ensure solutions follow least-privilege principles and protect enterprise data throughout retrieval, processing, storage, and output.
• Maintain strong working knowledge of Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, related APIs, and emerging enterprise AI capabilities.
• Understand the strengths, limitations, licensing considerations, and integration options of each platform.
• Evaluate new capabilities and identify where they can improve solution quality, reduce development effort, or expand supported use cases.
• Share lessons learned and reusable practices with AI enablement, platform, security, and engineering teams.

Benefits

• Health Insurance
• Retirement Plan
• Disability benefits
• Paid Time Off program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed