Sooch.ai is Hiring a Product manager, Gen AI platform Near Seattle, WA
Job DescriptionWe are seeking a Product Manager, Gen AI Platform to become an integral part of our team! You will develop and design GenAI product in accordance with GenAI governance standards. Responsibilities:
Create functional and appealing product designs
Prioritize product features based on marketing research and client feedback
Work with clients to refine designs and secure final approval for production
Collaborate with fellow designers and managers
Qualifications:
Previous experience in design, research, or other related field
Familiarity with production processes and materials
Strong presentation skills
Deadline and detail-oriented
Company DescriptionDemocratizing access to Generative AI and empowering a broader range of users to create, innovate, and optimize their workflows, we envision a platform that provides low-code/no-code capabilities. By abstracting the underlying technology and offering a user-friendly, drag-and-drop interface, our platform will enable users to build, customize, and deploy AI-driven workflows effortlessly. As part of the democratization, we are creating a new workflow engine that leverages advanced AI optimization algorithms to drive significant technological innovation. Specifically, our project will employ cutting-edge techniques such as Genetic Algorithms, Simulated Annealing, and Graph Completion Algorithms. These methods will enable us to develop a robust and efficient system that optimizes complex workflows in novel ways. Democratizing access to Generative AI and empowering a broader range of users to create, innovate, and optimize their workflows, we envision a platform that provides low-code/no-code capabilities. By abstracting the underlying technology and offering a user-friendly, drag-and-drop interface, our platform will enable users to build, customize, and deploy AI-driven workflows effortlessly. As part of the democratization, we are creating a new workflow engine that leverages advanced AI optimization algorithms to drive significant technological innovation. Specifically, our project will employ cutting-edge techniques such as Genetic Algorithms, Simulated Annealing, and Graph Completion Algorithms. These methods will enable us to develop a robust and efficient system that optimizes complex workflows in novel ways.