We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

POSITION SUMMARY

CVS Health is seeking a Senior ServiceNow AI Engineer, a platform engineering role responsible for enabling, scaling, and operating enterprise AI capabilities across the ServiceNow platform. This role focuses on Now Assist and Moveworks integration, delivering secure, governed, and reusable AI services that can be consumed consistently across HRSD, ITSM, ITOM, and broader ESM domains.

Operating within the ServiceNow Platform Engineering organization, this role emphasizes configuration‑first AI enablement, standardized patterns, and guardrails—ensuring AI solutions are scalable, measurable, and aligned with enterprise security, privacy, and governance standards.

Role Scope & Operating Model

• Scope: Platform‑wide (shared AI services across all ServiceNow products)

• Model: Central Platform Engineering (not embedded in a single product team)

• Primary AI Capabilities: Now Assist Skills, Now Assist Agents, Now Assist Agentic Workflows, Moveworks Agent to Agent Integration, AI Control Tower, Now Assist for Creator

• Engineering Approach: Configuration‑first, with selective scripting and integration development as needed

• Success Metrics (Examples).

• Adoption and enablement of Now Assist and Moveworks across ServiceNow domains.

• Reduction in manual handling time through AI assistance.

• Self‑service containment and deflection improvements.

• Stability and upgrade safety of AI configurations.

• Compliance with AI governance and audit requirements

What we expect of you

1) Enterprise AI Enablement (Now Assist & Moveworks)

• Configure, deploy, and operate Now Assist capabilities (Skills, Agents, Agentic Workflows, Agent to Agent Integration, AI Control Tower, Now Assist for Creator).

• Integrate and align Moveworks with ServiceNow experiences, ensuring seamless handoff, consistent intents, and enterprise‑approved patterns.

• Develop within platform‑level AI standards for enterprise re-use and scalability.

• Support Citizen Developer model for AI Enablement.

• Support ESM SDLC process (Development, Testing, Code Migration, Deployment)

2) Platform Architecture & Reusable Patterns

• Design and maintain reusable AI configurations, including Skills and Agents.

• Define reference architectures for common use cases across AI configurations.

• Ensure AI solutions align with ServiceNow platform architecture, performance expectations, and upgrade compatibility.

3) Configuration‑First Engineering with Selective Scripting

• Leverage out‑of‑the‑box and configurable AI features wherever possible to maximize maintainability and upgrade safety.

• Use scripting and custom logic only when required to extend capabilities, integrate systems, or enforce enterprise guardrails.

• Build and maintain integrations using Integration Hub, APIs, and event‑driven patterns to support AI‑initiated actions.

4) Responsible AI, Security, and Governance

Responsible AI Governance to ensure:

• Appropriate data access boundaries

• Role‑based controls and logging

• Human‑in‑the‑loop and escalation patterns

• Support architecture reviews, AI technical governance boards, and risk assessments for AI features.

• Document AI designs, data sources, and controls to support audit and compliance requirements.

5) Measurement, Optimization, and Observability

• Support the definition of and monitoring of platform‑level AI KPIs.

• Continuously tune prompts, intents, and configurations based on usage data and outcomes.

• Partner with product teams to validate AI value realization across domains.

6) Platform Operations & Lifecycle Management

• Establish operational runbooks for AI capabilities, including monitoring, incident response, and problem management.

• Manage AI feature lifecycle across environments (lower → production), including testing, releases, and upgra