Senior Product Manager, AI Agents Messaging

Senior Product Manager

At Zendesk, we strongly believe that to build a great product you have to have great people. We enjoy working with other smart focused people who care about both the product and the code they write. We value collaboration and getting new product capabilities in front of our customers frequently. We like and use agile processes and believe that pragmatism always triumphs over dogmatism.

We all own the product and enjoy the impact we have improving it.

We are currently looking for a Senior Product Manager who will lead a new Knowledge Graph team dedicated to ingesting and modeling content that will serve many of our flagship AI experiences. This team will be crucial to our Knowledge product which empowers organizations to create, manage, and share knowledge seamlessly, helping customers find answers quickly and efficiently. The integration of knowledge graphs will enhance our current capabilities, providing richer, more contextual information to improve user experience.

This role cuts across multiple teams and many levels of ownership, bringing together engineering and science teams working with rapidly developing technologies. The ideal candidate will be able to prioritize effectively, solve challenging problems, and have a strong experience with knowledge graph implementations, working with data science, natural language processing (NLP), optical character recognition (OCR), and document cleaning, all while working effectively to bring people together to achieve a critical mission.

• Create and own a knowledge graph roadmap:
  Own the vision and roadmap for Zendesk's knowledge graph initiatives, including the development of features that enhance content ingestion workflows and improve the flow and retrieval of structured and unstructured data
• Form and Develop a Team:
  Participate in forming a talented team focused on knowledge graph development, fostering a collaborative and innovative environment that encourages growth and creativity.
• Collaborate with Cross-Functional Teams:
  Work closely with engineering, data science, and design teams to build scalable solutions that leverage knowledge graphs for improved customer insights and experience.
• Drive Feature Development:
  Prioritize and manage the development of key features, ensuring they meet user needs and align with our overall product strategy.
• Communicate Vision and Progress:
  Clearly articulate the knowledge graph vision to stakeholders, including developers, upper management, and customers, keeping them informed and engaged throughout the development process.
• Conduct Product Research:
  Engage with customers and stakeholders to gather feedback, understand their needs, and iterate on product features to enhance usability and effectiveness.
• Oversee Data Quality and Governance:
  Ensure the integrity and quality of data within knowledge graph by implementing best practices for data ingestion, cleaning, and management.

• Experience in Product Management:
  Minimum of 5 years of experience in product management, particularly in SaaS environments, with a strong focus on data-driven products.
• AI/ML Product
  
  Experience:
  
  Familiarity with LLMs, RAG architectures, embedding models, or generative AI product development. You don't need to build the models, but you understand how they consume and surface knowledge.
• Content Processing at Scale:
  Experience with multi-format content ingestion — NLP, OCR, document cleaning — across diverse source types in a multi-tenant SaaS environment.
• Strong Product Instincts and Analytical Mindset: you know how to measure success and regularly monitor progress.
• Excellent Communication
  
  Skills:
  
  Outstanding verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Collaborative Approach: A team player who thrives in a collaborative environment and can influence and motivate cross-functional teams.
• Adaptability and Problem-Solving:
  Comfort with ambiguity and a proactive approach to solving complex problems.

• Knowledge Graph Expertise:
  Proven experience in knowledge graph development, semantic modeling, and content ingestion processes.
• Technical Proficiency:
  Familiarity with data science concepts, NLP, OCR technologies, and document cleaning techniques.