Overview: At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges. Being part of Zebra Nation means you are seen, heard, valued, and respected.

Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve. You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally.

Come make an impact every day at Zebra.

What We're Looking For: Executes and continuously improves the tooling, processes, and AI initiatives that govern how Zebra’s support knowledge performs across self-service and AI-driven support experiences, with accountability for domain-level outcomes. Owns defined workstreams end-to-end within assigned domains — including knowledge gap execution, AI performance monitoring, and prompt refinement — and operates as the primary driver of knowledge system effectiveness. Works within frameworks established by the Content Strategy Lead and senior team members, translating strategy into execution by identifying issues, prioritizing actions, directing resolution, and validating outcomes in collaboration with Technical Content Management (TCM), Knowledge Management (KM) Operations, subject matter experts (SMEs), and support teams.

Owns outcomes within assigned areas, including setting priorities, defining actions, and ensuring results are delivered.

Key Responsibilities Tooling & Process Enhancement: Implement, configure, and optimize knowledge and AI content tooling within assigned areas. Proactively identify tooling and process improvement opportunities based on performance data, and recommend enhancements with clear expected impact to deliver measurable improvements in content delivery.

AI Performance & Optimization: Independently monitor AI content performance signals—including retrieval gaps and answer quality—and assess AI-generated responses for accuracy, grounding, and consistency. Apply human-in-the-loop validation, direct corrective actions, and continuously write, test, and refine prompts to improve how knowledge is surfaced.

Knowledge Gap Execution & Content Direction: Drive the knowledge gap strategy by conducting regular audits to identify outdated or underperforming content. Provide clear, prioritized direction to content owners and SMEs on required updates and fixes, tracking resolution to ensure measurable improvement and alignment with defined standards. Standards, Discoverability & Localization: Uphold content standards, metadata schemas, and taxonomy frameworks, identifying gaps and driving updates through appropriate governance channels.

Apply SEO and AI discoverability principles (GEO, AEO) to optimize retrieval, while ensuring content structures enable high-quality localization and flagging systemic issues for resolution. Cross-Functional Collaboration & Validation: Partner with Product, Engineering, Content Management, KM Operation, and Support Operation teams to ensure knowledge initiatives are accurate, timely, and contribute to support efficiency. Continuously validate that improvements result in better self-service success, reduced support friction, or an improved agent experience.

Mentorship & Team Development: Provide day-to-day direction, guidance, and support to junior team members, ensuring the overall quality of team output and supporting their professional development within the digital content field.

Required Qualifications Education: Bachelor’s degree in Information Science, Information Management, Computer Science (AI/Data Science track), or a related field, or equivalent practical experience.

Experience: 3–5 years of experience in content strategy, content operations, or knowledge management within an enterprise or high-volume support environment. Retail/E-commerce Domain Knowledge: Solid understanding of how structured content and product information drive discoverability and self-service outcomes at scale within retail or e-commerce operations.

AI & Systems Expertise: Demonstrated hands-on experience with AI-powered content tools (e.g., RAG, Copilots, or Chatbots). Must understand how structured content and metadata influence answer quality and retrieval optimization.

Prompt Engineering: Proven ability to write, test, and refine prompts and guidance for AI tools to improve how knowledge is surfaced in support experiences.

Content Governance: Experience executing within knowledge governance frameworks—applying content standards, metadata schemas, and taxonomy principle