Responsibilities
- 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
- ~10–12h/week for 12 weeks
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
Work Arrangement
Remote (Worldwide)
Team
Structure: senior builders team up to validate real B2B problems
Additional Information
- participation ticket after acceptance to ensure commitment
- ~10–12h/week for 12 weeks
