Location: Remote (USA)
Duration: 12+ months
We're seeking an experienced technical leader to transform how enterprise knowledge is managed, trusted, and leveraged across the organization. This role will lead the evolution of our knowledge ecosystem from a traditional content repository into a scalable, measurable, AI-enabled platform that powers search, automation, decision‑making, and intelligent agent experiences.
This is a highly visible leadership position at the intersection of Knowledge Management, Generative AI, information architecture, and product strategy. You'll work closely with business stakeholders, architects, engineers, and content owners to build capabilities that improve how knowledge is created, governed, discovered, and consumed across the enterprise.
The ideal candidate combines strong technical depth with strategic product leadership and has successfully delivered AI‑driven solutions from concept through adoption.
What You'll Do
Build a Trusted and Measurable Knowledge Ecosystem
- Define and implement KPIs that measure content quality, accuracy, freshness, ownership, governance compliance, and AI readiness.
- Establish processes and reporting that provide visibility into the reliability and health of enterprise knowledge.
- Drive automation of content governance, review cycles, and lifecycle management.
- Create actionable insights that help stakeholders identify stale, unreliable, or unowned content and improve overall knowledge quality.
Lead AI-Powered Knowledge Transformation
- Define the vision, architecture, and roadmap for AI‑enabled knowledge solutions.
- Design and develop agentic AI capabilities that can retrieve, connect, and deliver trusted enterprise information.
- Partner with engineering and architecture teams to prototype, validate, and deploy AI‑powered experiences.
- Establish standards for retrieval, grounding, security, evaluation, and governance to ensure responsible and effective AI adoption.
- Translate emerging AI technologies into practical business applications and measurable outcomes.
Develop a Scalable Enterprise Knowledge Framework
- Create enterprise‑wide standards for metadata, taxonomy, content ownership, governance, and lifecycle management.
- Enable business teams to manage knowledge at scale while maintaining consistency, quality, and trust.
- Design frameworks that support knowledge consumption across search, workflows, automation platforms, and AI experiences.
- Establish repeatable processes that can be adopted across multiple business functions and teams.
Drive Cross‑Functional Program Leadership
- Lead complex initiatives involving business stakeholders, technical teams, and executive leadership.
- Translate business objectives into scalable technical solutions.
- Prioritize roadmaps, align stakeholders, and drive adoption of new capabilities.
- Measure business impact and continuously optimize solutions based on performance data and user feedback.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, Business, or a related field, or equivalent professional experience.
- Experience leading enterprise‑scale AI, Generative AI, knowledge management, search, or digital transformation initiatives.
- Demonstrated success delivering solutions from strategy and design through implementation, adoption, and measurement.
- Strong understanding of Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), semantic search, vector search, and agentic AI architectures.
- Experience designing knowledge retrieval, grounding, and information access strategies for AI‑enabled solutions.
- Knowledge of enterprise information architecture, metadata, taxonomy design, governance, and content lifecycle management.
- Experience integrating enterprise systems through APIs, connectors, data pipelines, and modern cloud‑based architectures.
- Proven ability to lead cross‑functional programs and influence stakeholders across business and technology organizations.
- Strong analytical and problem‑solving skills with a focus on measurable outcomes.
Preferred Technical Experience with the following:
Artificial Intelligence & Search
- Retrieval‑Augmented Generation (RAG)
- Agentic AI and multi‑agent systems
- Semantic and enterprise search
- Embeddings and vector databases
- AI evaluation frameworks and grounding strategies
Enterprise Technology & Integration
- APIs and microservices
- Structured and unstructured data environments
- Authentication, permissions, and security models
- Cloud platforms and modern architecture patterns