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Monk is an AI-native accounts receivable platform helping B2B companies get paid faster. The AR stack is outdated—finance teams still use spreadsheets and decade-old software to manage trillions in outstanding invoices. Monk is rebuilding this space with AI, speed, and craftsmanship, already managing over $1B in AR for enterprise customers.
As the first Sales Engineer at Monk, you will be the technical bridge between enterprise customers and the product. You'll assess customer requirements, determine Monk's fit across use-cases and ROI, and work hands-on with implementation teams to get large, complex customers live. You'll design and prototype agentic solutions tailored to customer workflows—diving deep into ERP systems one moment and building novel AI-powered experiences the next.
Key responsibilities include: acting as the customer's voice to assess requirements and technical capability; building creative proof-of-concepts that showcase Monk's agentic sophistication; prototyping and shipping financial products with enterprise clients; and constructing perfectly tailored experiences for AR workflows (collections, cash application, deductions, disputes, integrations). You'll shape revenue strategy by identifying new products and scaling solutions for existing customers.
You bring 5+ years shipping production full-stack products with deep TypeScript fluency. You're product-obsessed, customer-centric, and comfortable with ambiguity in high-stakes agentic systems. Experience with modern web infrastructure (Next.js, Vercel, Supabase) is expected. You're an owner who figures out what needs to exist and builds it autonomously, leveraging AI throughout your work. You thrive in person at the Flatiron office in NYC (note: posting says San Francisco but description emphasizes NYC Flatiron location—clarification needed).
Monk values ownership and craft, speed and urgency (shipping daily), and radical clarity. The company is backed by leading investors, founded by experienced entrepreneurs with successful exits, and operates with an engineering-first culture. This is an opportunity to work at the frontier of applied AI, see your work reach production quickly, and learn from a team of second-time founders.
