Job Description:
• Validate a B2B problem where AI creates measurable value (time, cost, risk)
• Define MVP that’s product-first (not “cool model-first”)
• Design the data approach (collection, labeling, evaluation, monitoring)
• Ship a reliable prototype/MVP (APIs, pipelines, guardrails, feedback loops)
• Craft investor-ready tech narrative (moat, data advantage, roadmap)
Requirements:
• 7+ years in software engineering with strong AI/ML or data product exposure
• Experience shipping to production (MLOps basics, monitoring, reliability)
• Strong product instinct: clarity on what “good enough” looks like for an MVP
• Founder mindset; you want ownership and upside, not a service role
Benefits:
• 12-week sprint to go from insight → MVP → iteration
• Weekly accountability + execution cadence ( ~10–12h/week )
• 500+ mentors including B2B, product, GTM, fundraising specialists
• 440+ alumni startups / 40+ countries for learning + intros
• CTO toolkit for AI ventures: scope, evaluation, deployment, “moat” story