Senior Workforce AI Solutions Engineer

Verisk Analytics • Jersey City, NJ

4d • Remote

About The Position

Join Verisk's Workforce Technology Services organization as a Workforce AI Solutions Engineer, partnering 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 related technologies. This role serves as technical lead and primary owner for a queue of business-submitted AI solution requests that require light-to-moderate implementation effort. The engineer leads each engagement and remains hands-on with solution design, development, testing, and delivery alongside a collaborating coworker. Work may include workflow automation, AI agent development, system integrations, document intelligence, knowledge retrieval, process simplification, and productivity optimization. A partner intake and triage team handles simple questions, training needs, and requests requiring clarification before qualified implementation requests reach this role.

The role accelerates measurable business value from enterprise workforce AI investments by designing solutions that improve productivity, reduce manual effort, and simplify business processes. It acts as a technical advisor and solution architect for workforce AI technologies and establishes reusable agents, skills, integrations, MCP components, and solution patterns. The engineer also drives responsible AI adoption in accordance with enterprise security, governance, privacy, and compliance requirements.

The successful candidate combines curiosity about emerging AI capabilities with disciplined enterprise engineering. They can move between business-process and technical-design discussions, 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.

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 select the appropriate method for a 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

• 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 from business units across the company.
• Partner with intake and triage to confirm scope, readiness, ownership, dependencies, and delivery path, then lead execution with the assigned coworker.
• Work 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 implementation documentation, knowledge transfer, and transition to an ongoing support model.
• Design AI-enabled workflows, agents, automations, and business process improvements.
• Select platforms and implementation approaches based on business needs, technical fit, security, maintainability, and cost.
• Build solutions using simple builder experiences, low-code platforms, and pro-code development when needed.
• Create reusable design patterns, templates, components, and engineering standards to 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 including 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.
• 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.
• Follow least-privilege principles and protect enterprise data throughout retrieval, processing, storage, and output.
• Maintain working knowledge of Microsoft Copilot, Copilot Studio, Claude, ChatGPT Enterprise, related APIs, and emerging enterprise AI capabilities.
• Understand platform strengths, limitations, licensing considerations, and integration options.
• Evaluate new capabilities for opportunities to 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.

What This Job Offers

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