About Kaso

KASO is the world's first AI-powered group purchasing (GPO) for the food industry.
We build AI agents to aggregate demand from restaurants and negotiate chain-level pricing with food suppliers.

We started with KASO Order, moving thousands of restaurant-supplier orders from WhatsApp and phone calls into clean, reliable digital workflows which are used by 5000+ restaurants like Burger King, Tim Hortons, Caribou Coffee and many more.

We are backed by Y Combinator, Global Founders Capital, MSA Capital, Seedra, Spades and others alongside founders from Careem, Talabat, Delivery Hero, Tabby, and more. 

Food is one of the world's biggest industries, and it still operates like it's 1995. We're a small team with AI agents in production and a head start no one else has. Come build the thing that fixes it at Kaso.

About the role

You’ll contribute to the technical backbone that turns a traditionally ops-heavy GPO business into a scalable software platform. The goal is to make it possible for independent restaurants to buy with the power of a chain, while reducing reliance on manual operations. 

• The problem you'll own: Replace manual, people-dependent procurement workflows with trustworthy software that is accurate, scalable, and self-serve
• The systems you'll build: Contribute to the technical platform, including tech architecture, order workflows, matching and pricing logic, data foundations, and automation layers that support operations and user experience
• The change you’ll drive: Turn messy food procurement processes into reliable product workflows
• What success looks like: The business scales without losing pricing accuracy, order integrity, or operational trust, and the team can serve more restaurants with less manual work

Must have

• Backend depth - built and scaled production systems, with proven ability to architect and orchestrate multi-service applications
• Stack fluency - deep hands-on expertise in TypeScript/Node.js and Python, plus React, Flutter or similar on the frontend
• Data modeling - modeled messy real-world data into trustworthy systems at scale
• Think in AI automation - track record of automating operations-heavy processes with AI, avid use of state-of-the-art AI development tools as Claude Code
• Product judgment - led E2E architecture through launch with a bias for speed and impact; made pragmatic tradeoffs to solve user problems

Nice to have 

• Domain - built B2B platforms such as procurement, marketplaces, or supply chain, ideally in a startup or scale-up environment
• Money movement - worked on billing, invoicing, payments, or reconciliation systems
• Team leadership - scaled and led technical teams through architecture, code review, and engineering standards

Perks

• Competitive salary and meaningful equity
• Real AI work in production, not prototypes
• A business past product-market fit and into scaling
• Low-ego, high-ownership team culture
• Direct access to founder and leadership team