Hands-on founding engineer building a production Shopify app, storefront widget, video upload flow, and AI extraction pipeline. Ship, harden, and operate full-stack systems, ensure reliability and conversion-focused UX, and scale tooling for self-serve merchant onboarding.
Who we are
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.
Vidably 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.
About the role
This is a hands-on, jump-into-anything role on a small, talented team. You'll help build the AI-powered evidence layer for commerce, making Vidably self-serve and reliable across real Shopify storefronts. Candidates must currently be based in the Bay Area. Relocation will not be an option for this role.
Responsibilities for the Role Include:
- Build and ship across the full stack: Shopify app, storefront widget, AI extraction pipeline, internal tooling
- Harden a live Shopify app and storefront integration 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 raw buyer video into structured product evidence at scale: AI extraction, review/approve/publish, and self-serve tooling
What Success Looks Like:
- Onboarding new customers becomes boring and repeatable
- Founder minutes per merchant drops materially because workflows are productized
- We can scale customers without bespoke engineering per store
Required Qualifications Include:
- You've shipped to production across the stack and you close loops fast — you design, build, debug, and operate
- Strong fundamentals: performance, reliability, security, and product/UX judgment (especially on conversion-sensitive surfaces)
- AI-native builder: you ship production code with agentic tools (Cursor, Claude Code, Codex CLI, similar).
- You use AI for speed, keep quality high with tests/CI/observability, and can debug when AI output is wrong
- Thrive in ambiguity and a very small-team environment.
- You're excited to learn new tools and domains fast, and you jump into whatever needs doing
Nice to Have Skills Include:
- Shopify apps/theme integration experience, or embedded widget/SDK experience in hostile third-party environments
- Video pipeline familiarity (Mux or similar)
- Experimentation/analytics rigor: clean event design, integrity checks, debugging
AI Fund Palo Alto, California, USA Office
Palo Alto, CA, United States, 94303
Similar Jobs
Information Technology • Professional Services • Security • Consulting
Lead hands-on architecture and development for greenfield digital products and the engineering platform supporting them. Build full-stack solutions, distributed backends, cloud infrastructure, CI/CD pipelines, reusable services, Kubernetes and infrastructure-as-code capabilities. Establish observability, quality, and engineering standards while mentoring engineers and partnering with product and design teams to improve delivery velocity and autonomy.
Top Skills:
AWSCi/CdDockerGCPGithub ActionsGitlab CiGoGrafanaInfrastructure As CodeJaegerKubernetesPrometheusPythonReactTerraformTypescript
Artificial Intelligence • Machine Learning • Business Intelligence • Financial Services • Big Data Analytics • Manufacturing
As a Founding Full-Stack Engineer, you'll build AI-native systems, integrating LLMs, prototyping quickly, and collaborating to influence engineering standards and culture.
Top Skills:
FastapiNext.JsNode.jsPythonReactTypescript
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software • Defense Technology
Integrate, validate, and deploy autonomy software across simulations, hardware-in-the-loop environments, and flight platforms. Configure sensors, interfaces, and platform adapters; develop integration tooling, deployment scripts, and configuration management; troubleshoot system behavior using logs, telemetry, and rosbag data; optimize CI/CD workflows; validate requirements and interface contracts; and collaborate with engineering, product, DevOps, and customer teams to deliver reliable autonomous systems.
Top Skills:
Autonomous SystemsC++Ci/CdCommunication InterfacesEmbedded SystemsHardware-In-The-Loop (Hil)MiddlewareNetworkingOperating SystemsPythonRadio CommunicationsRoboticsRosRosbagSensor DriversSimulation ToolsSoftware-In-The-Loop (Sil)
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
