Basic and Required Qualifications:

Technology Stack:
• Enterprise and Saas Experience
• Worked on ML/AI cloud native ML products, Data Science tools, and ecosystem 
• Hands-on experience building and running highly technical and scalable teams
• Work with product/customer teams on how machine learning can make their product or system better
Management/Leadership Stack:
• Experience building and leading expert machine learning teams that have routinely launched new products and features that drive significant revenue and engagement with machine learning.
• Experience developing machine learning products and capabilities in a cloud environment with a good understanding of the product and sales side of the business
• Experience with prioritizing and adding new machine learning-based features and capabilities,  launching new products to drive revenue
• Capacity plan pre-sales and post-sales support from within the team. Drive horizontal engineering efforts that improve the efficiency of the pre-sales and post-sales organizations.
• Work with multiple stakeholders within Product, Sales, and Engineering and with Customers to plan releases.
Customer Advocacy Stack:
• Candidate should have the business, strategic, and technical background to understand the customer needs to innovate new features and  product ideas 
• Visionary thinker: Should be able to develop plans for customer acquisition and growth plan, strategic partnership and should be able to interact with internal and external leadership to be successful.
• Great presentation skills - for our typical audience - technical and executive staff for product demos as well as whiteboard machine learning solutions to business problems

Preferred / Good to have Qualifications

• Big and small company experience
• Open source Saas product experience
• GNN/Graph Experience
• Closely worked with product and sales and should be able to update product/feature/customer updates to the executive staff