Senior Product Manager, NewsBreak

• Experience: 3+ years of experience as a Product Manager, preferably in a B2C or B2B SaaS company focused on creator tools, video technology, or AI/ML
• AI/ML Fluency: Demonstrated experience working with AI/ML engineering teams to define and launch features powered by machine learning models. You must be comfortable discussing model limitations, data requirements, and MLOps principles
• Analytical Skills: Proven ability to use data (SQL, Amplitude, Mixpanel, etc.) to drive product decisions and measure success
• Communication: Exceptional written and verbal communication skills, with the ability to articulate complex technical and user problems to diverse audiences
• Technical Acumen: Strong understanding of modern web and cloud technologies (e.g., React, Python, APIs, AWS/GCP) sufficient to engage in technical discussions with engineers

Desirable

• We are seeking a visionary and execution-focused Product Manager to own the strategy and roadmap for our suite of AI video tools. You will be the voice of the customer, bridging the gap between content creator needs, cutting-edge AI research, and engineering execution
• This role is central to our success, requiring a blend of strategic thinking, deep user empathy, and technical fluency in the AI/ML space
• Product Strategy & Roadmap: Define and champion the product vision, strategy, and detailed roadmap for one or more core AI video features (e.g., Long to Shorts, AI Commentary, or new monetization features)
• User Discovery: Conduct continuous user research, interviews, and data analysis to deeply understand the pain points and workflows of content creators, social media managers, and video editors
• Execution & Delivery: Translate product strategy into clear, concise Product Requirements Documents (PRDs), user stories, and acceptance criteria. Work closely with the Full Stack and AI Engineering teams to ensure timely and high-quality feature delivery
• AI Feature Definition: Collaborate with the AI/ML team to define the input, output, and success metrics for new AI models, ensuring they solve real user problems and are production-ready
• Performance Analysis: Define, monitor, and analyze key product metrics (e.g., usage, retention, conversion, and feature adoption) to inform iterative product improvements and strategic decisions
• Go-to-Market: Partner with marketing, sales, and customer success teams to develop and execute successful go-to-market plans, including defining pricing and packaging for new features