The opportunity
There's an enormous difference between building a Fin demo and deploying Fin in production. A Solutions Engineer can stand up an impressive AI agent demo in an afternoon.
What you'll do
Own the Fin demo platform end-to-end. Multi-tenant mock workspaces, seeded: data, configuration, reset infrastructure, and guardrails that make demos reliable, fast, and safe.
Build first-class demo features into Fin itself. Create UI and workflows so: SEs can spin up, reset, and tailor demo accounts in minutes - not hours.
Use AI to prepare demos. Use Fin itself (and other models) to research: prospects, synthesize realistic org structures and conversations, and auto-configure demos for specific verticals and use cases.
Let SEs move faster. Build templates, libraries, and scripting hooks so SEs: can compose complex demo scenarios with guardrails - not raw access to production.
Show Fin across every surface it touches. Web Messenger, mobile SDKs, voice,: email, Slack, API-driven workflows. The demo should match how customers will actually deploy.
Partner with Enablement. Design hands-on training, demo libraries, and: certification paths that ramp SEs and AEs faster than anywhere else in the industry.
What they're looking for
- Stay one step ahead of the product roadmap. When a new Fin capability ships,: the demo for it should already exist. This happens with strong collaboration with our product teams directly.
- Codify what works. Turn patterns from the field into tools, templates, and: playbooks the whole GTM org can use.
- + years building software in a customer-facing technical role: Solutions Engineering, Developer Relations, Founding Engineer, or similar.
- Hands-on AI/LLM product experience. You've built with LLMs, you understand: RAG, tool use, agents, and evals, and you know the practical limits of current models.
