Engineer in Residence: Live Selling Copilot

Live commerce is bottlenecked by host capacity and operational chaos. Great sellers win on personality and community, but they still have to multitask like air-traffic controllers: managing chat, pacing listings, handling inventory, answering niche questions, and doing post-show follow-up. This role is to build a LiveOps Copilot: a human-first AI producer that runs backstage for live commerce sellers, keeps the host front and center, and automates the operational work around the show.

What You'll Build

• A backstage producer cockpit that clusters chat, drafts or sends guardrailed replies, and surfaces the highest-value audience questions in real time.
• A listing and inventory control towebaer that helps hosts manage sequencing, pinned items, bundles, and oversell or stale-listing risk during the show.
• A real-time product research layer that answers unknown questions from seller notes, listing data, historical Q&A, and trusted category sources.
• Multilingual translation and localized reply support so hosts can engage cross-border audiences without losing flow.
• A lightweight post-show repurposing workflow that turns streams into reusable clips, Q&A moments, and listing assets.

What You'll Do

• Build the end-to-end real-time system across chat ingestion, retrieval, guardrails, operator UX, listing controls, and post-show outputs.
• Work with one of our large LPs as your build/design partner to identify the right pilot category, host set, data path, and success metrics for the MVP.
• Design the automation ladder from draft support to host-controlled agentic replies without undermining authenticity or seller trust.
• Make decisions about latency, guardrails, disclosure, and escalation so higher-autonomy features are safe and useful.
• Work with AI Fund's build team on product wedge, technical risk, and the path from pilot to a broader live-commerce OS.

What You Need

• Strong full-stack execution, especially on real-time systems, operator workflows, and AI-assisted products.
• Demonstrated experience building GenAI products with retrieval, tool use, guardrails, and production feedback loops.
• Product judgment for human-in-the-loop automation where the right answer is usually to remove busywork rather than replace the human outright.
• Ability to move quickly with external design partners and translate ambiguous feedback into working product decisions.
• You actively use AI coding assistants and modern GenAI tools as part of your build workflow.
• US work authorization. We are unable to sponsor visas for this role.

Helpful but Not Required

• Experience with live commerce, creator tools, marketplaces, video products, or seller operations.
• Experience with multilingual UX, moderation systems, or low-latency chat infrastructure.
• Founder or founding engineer experience.

Who This Is For

• A builder who likes real-time operator products, tight feedback loops, and markets where authenticity matters.
• Someone who sees the wedge in backstage tooling now, while building the data and control layer that could support deeper automation later.

What to Know Upfront

• This is a 12-week, full-time, on-site residency in Mountain View, California.
• Not every residency becomes a company. The goal is to pressure-test the idea quickly and honestly with real users and customers.
• You will be building an AI Fund idea, not bringing your own startup idea into the program.
• The process typically includes a Builder Event or equivalent working conversation, then a 48-hour Build Challenge, then panel review with AI Fund build leadership.
• The compensation is intentionally modest during the residency because the upside, if the idea works, is a founder-level role.

Compensation

$10,000/month for 12 weeks ($30,000 total). This is a contract role during the residency. If the build leads to a funded company, the next step is a founder-level role with meaningful equity upside.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.