AI Tooling Engineer

**🚀 Join the Future of Commerce with Whatnot!** Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it’s trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We’re building live commerce at a scale that’s never been done in the West, and there’s no playbook to copy. The people here are shaping how an entirely new industry develops.

As a remote co-located team, we’re inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.

We’re one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.

**💻The Role** We’re looking for an AI Engineer to build the internal tools, prototypes, and business workflows that put AI into the hands of every team at Whatnot. You’ll own ambiguous, cross-org bets end-to-end: finding real problems, shipping working software fast, hardening what works, and scaling how Whatnot gets value out of AI. You’ll partner with Whatnot’s AI Platform and Developer Tools teams to leverage their systems, add new functionality, and find ways to accelerate adoption by non-technical team members.

This is a high-velocity, high-judgment builder role. You’ve shipped a lot of apps and prototypes—you’re someone who can sit with a CX lead or an ops manager, understand their workflow in an afternoon, and have a working prototype in their hands by the end of the week. You create leverage for yourself by building on top of 3rd party tools where it’s advantageous but also know how to navigate lower-level interfaces where necessary. You also operate above any single project: you help decide where the opportunities are, define the reusable patterns and infrastructure others adopt, and raise the bar for how the whole company builds with AI. You move fluidly across the stack (frontend, backend, data, and the AI layer) and are deeply fluent in the current generation of AI tools and the production patterns around them—prompt engineering, RAG, MCP, agents, and evals.

This is not a model-training or research role. You won’t be training models—you’ll be building the tools, workflows, and integrations that make off-the-shelf AI dependable and useful inside Whatnot’s systems and processes.

**✅ What You’ll Do**

• Own ambiguous, cross-org AI bets end-to-end—identify the highest-leverage problems across the company, decide what to build, and drive it from prototype to durable production tool
• Build and ship a high volume of internal apps, prototypes, and automations—going from a vague problem to a working tool in days, then iterating with users toward production quality
• Define the reusable patterns the org builds on, including reference architectures, internal libraries, MCPs, and skills/plugins that let others move faster and safer
• Embed directly with teams across CX, Trust & Safety, Ops, and GTM to find high-leverage problems, then build the solution alongside them
• Integrate AI tools with internal systems and data sources via APIs, connectors, and event-driven workflows so automations act on real state, not toy inputs
• Scale the leverage—package successful builds into reusable skills and playbooks, and level up the whole company through enablement sessions, boot camps, and mentorship of other builders
• Stay ahead of the AI landscape, evaluating and bringing in new models, tools, and patterns as the ecosystem evolves, and making the build-vs-buy calls

**👀 Who You Are**

• A prolific builder with senior judgment—you ship fast and iterate with real users, and you know where not to invest; you measure yourself by problems solved, tools adopted, and leverage created
• Deep applied-AI fluency—extensive hands-on experience building with the current generation of LLM products (Anthropic, OpenAI, Google) and popular agent frameworks (Cowork, Glean, Dust, etc) and the production patterns around them: prompt engineering, RAG, MCP, agents, and evals
• Systems-integration chops—you’ve connected AI to real data and tools through APIs, webhooks, and connectors, and you …