Founding CTO/Lead Engineer (AI-Native)

$370K/yr

Job Description

Vidably is building the evidence layer for commerce: verified buyer video, structured with AI, and tied to outcomes.

UGC video contains more product truth than specs, studio media, or text reviews because it shows fit, feel, use-case, and tradeoffs in real contexts. It is how people actually decide what to buy.

Today, the most impactful buyer video lives on platforms like TikTok and Reels, disconnected from product pages, outcomes, and brand control. Vidably brings that content onto owned commerce surfaces, uses AI to turn it into structured, SKU-level evidence, and measures what actually drives conversion. We share incremental value with creators, which unlocks far more high-quality buyer video and a system that learns what matters for each product.

This is the missing input for shopping agents. The same signals humans use to buy confidently are the signals an agent needs to recommend, compare, and explain products with real evidence, not guesswork.

Visibly is backed and supported by AI Fund. Founded by Andrew Ng, AI Fund is backed by over $370 million. As a venture studio, AI Fund works alongside entrepreneurs, venture funds, and corporate partners to build new companies rapidly and increase their odds of success.

This is a CTO-scope, hands-on role. You will own engineering end-to-end and make Vidably self-serve and reliable across real Shopify storefronts. Real storefronts are messy. Legacy themes and script conflicts are normal. We design for that.

Responsibilities for the Role Include:

Own the codebase and technical direction: architecture, quality bar, shipping cadence, production reliability

Own and evolve a live Shopify app and storefront integration, hardening it across OS 2.0 and legacy theme realities with safe rollouts and easy rollback

Extend the mobile web creator upload flow with Mux: QR → prompt → record/upload → consent → submit

Turn content readiness from manual workflows into product: review/approve/publish, SKU mapping, internal tooling to automation