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Senior Product Manager (Data, Unstructured Data Management & RAG)
We are looking for a Senior Product Manager with expertise in Data Management and Retrieval-Augmented Generation (RAG) to help drive our RAG-related product direction. The successful candidate will be responsible for shaping the strategy, roadmap, and execution of key data-focused initiatives, driving innovation while balancing the needs of two distinct user personas: content managers and data professionals.

In this role, you will own the development and evolution of data-driven features, enabling our customers to extract value from both structured and unstructured data while leveraging the power of AI-driven content and insights.

Additional Responsibilities:

• Be the internal and external advocate for data-centric initiatives, acting as the expert in unstructured data, RAG, and data management features.
• Drive innovation around AI-driven content retrieval and unstructured data analytics to help customers extract actionable insights efficiently.

Communication, Roadmap, and Planning

• Create product updates that inform customers of newly released data management and AI-based features, ensuring timely communication and alignment with the overall platform strategy, acting as the primary owner of our RAG-related product features.
• Work cross-functionally to communicate upcoming features to internal teams (Sales, Marketing, Customer Success).
• Attend customer meetings, help troubleshoot product issues, and provide strategic input on how to achieve business goals with our unified platform, with a focus on data-related challenges and opportunities.
• Develop and present product information that ensures internal alignment among stakeholders and outlines new data-related features, ensuring all departments have the necessary context to deliver a successful whole-product launch.
• Work closely with leadership to develop the team’s roadmap, prioritizing data and AI-driven features that align with the unified platform vision.
• Act as the primary educator on RAG and AI-related product features, ensuring peer PMs and teams understand the underlying technology and its impact on product innovation and strategy

What Shelf Offers:

• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software

Why Shelf

• GenAI will be at least a $4 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale
• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• Weve been helping our customers prevent knowledge mismanagement since our founding in 2017
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

About Shelf

There is No AI Strategy without a Data Strategy. Getting GenAI to work is mission critical for most companies but 90% of AI projects havent deployed. Why? Poor data quality - it is the #1 obstacle companies have in getting GenAI projects into production.
Weve helped some of the best brands like Amazon, Mayo Clinic, AmFam, and Nespresso solve their data issues and deploy their AI strategy with Day 1 ROI.  
Simply put,  Shelf unlocks AI readiness.   We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers. 

Shelf is partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other big tech players who are bringing GenAI to the enterprise. 

Our mission is to empower humanity with better answers everywhere.

• Proven experience (3+ years) as a Product Manager or Senior Product Manager,  familiar with data management, and a track record of driving data-heavy product features from concept to launch.
• Experience with Retrieval-Augmented Generation (RAG) and a solid understanding of AI-driven search, content retrieval, and analytics throughout all phases of R&D.
• Experience with Snowflake, Databricks, or other data platform technologies, and how they integrate with product development.
• Strong understanding of the needs of data professionals (e.g., data scientists, data engineers) and content managers, and the ability to create products that cater to both personas.
• Demonstrated ability to write clear and detailed product requirements and user stories, particularly for data-centric products.
• Excellent communication and collaboration skills, able to work effectively with engineering, design, and other cross-functional teams.
• Familiarity with modern product management tools such as JIRA, Confluence, Aha!, etc.
• Experience using metrics and customer feedback to inform and iterate on product development decisions.

As a plus

• Familiarity with AI/ML models, NLP, and machine learning pipelines.
• Experience with large-scale data systems, particularly those that handle unstructured data and content analytics.

Senior Product Manager (Data, Unstructured Data Management & RAG)
We are looking for a Senior Product Manager with expertise in Data Management and Retrieval-Augmented Generation (RAG) to help drive our RAG-related product direction. The successful candidate will be responsible for shaping the strategy, roadmap, and execution of key data-focused initiatives, driving innovation while balancing the needs of two distinct user personas: content managers and data professionals.

In this role, you will own the development and evolution of data-driven features, enabling our customers to extract value from both structured and unstructured data while leveraging the power of AI-driven content and insights.

Additional Responsibilities:

• Be the internal and external advocate for data-centric initiatives, acting as the expert in unstructured data, RAG, and data management features.
• Drive innovation around AI-driven content retrieval and unstructured data analytics to help customers extract actionable insights efficiently.

Communication, Roadmap, and Planning

• Create product updates that inform customers of newly released data management and AI-based features, ensuring timely communication and alignment with the overall platform strategy, acting as the primary owner of our RAG-related product features.
• Work cross-functionally to communicate upcoming features to internal teams (Sales, Marketing, Customer Success).
• Attend customer meetings, help troubleshoot product issues, and provide strategic input on how to achieve business goals with our unified platform, with a focus on data-related challenges and opportunities.
• Develop and present product information that ensures internal alignment among stakeholders and outlines new data-related features, ensuring all departments have the necessary context to deliver a successful whole-product launch.
• Work closely with leadership to develop the team’s roadmap, prioritizing data and AI-driven features that align with the unified platform vision.
• Act as the primary educator on RAG and AI-related product features, ensuring peer PMs and teams understand the underlying technology and its impact on product innovation and strategy

What Shelf Offers:

• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software

Why Shelf

• GenAI will be at least a $4 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale
• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• Weve been helping our customers prevent knowledge mismanagement since our founding in 2017
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

About Shelf

There is No AI Strategy without a Data Strategy. Getting GenAI to work is mission critical for most companies but 90% of AI projects havent deployed. Why? Poor data quality - it is the #1 obstacle companies have in getting GenAI projects into production.
Weve helped some of the best brands like Amazon, Mayo Clinic, AmFam, and Nespresso solve their data issues and deploy their AI strategy with Day 1 ROI.  
Simply put,  Shelf unlocks AI readiness.   We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers. 

Shelf is partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other big tech players who are bringing GenAI to the enterprise. 

Our mission is to empower humanity with better answers everywhere.

,[Product Features and Delivery, Own the data-centric features of the assigned team and be the go-to person for product-related activities, with a specific focus on Data Management and RAG applications., Elicit and transform business requirements for data-driven initiatives (e.g., analytics, AI-based content insights) into detailed engineering specifications, ensuring clarity and alignment across teams., Split product features into user stories that drive value for both content managers and data professionals, with an emphasis on advanced analytics and AI-driven retrieval capabilities., Work closely with the design team to create UX and UI designs that focus on delivering user value., Help create and review customer-facing guides, focusing on RAG workflows, AI-driven product features, and general new data management capabilities., Define and track Product Metrics that provide insights into product usage and adoption, particularly for data management, content analytics, and RAG-based functionality. Requirements: Data management, Snowflake, Databricks, Product development, User stories, Jira, Confluence, AI/ML models, NLP, Machine learning Tools: .

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