About Groupon
Groupon is a marketplace where customers discover new experiences and services everyday and local businesses thrive. To date we have worked with over a million merchant partners worldwide, connecting over 16 million customers with deals across various categories. In a world often dominated by e-commerce giants, we stand out as one of the few platforms uniquely committed to helping local businesses succeed on a performance basis.
Groupon is on a radical journey to transform our business with relentless pursuit of results. Even with thousands of employees spread across multiple continents, we still maintain a culture that inspires innovation, rewards risk-taking and celebrates success. The impact here can be immediate due to our scale and the speed of our transformation. We're a "best of both worlds" kind of company. We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact.
Groupon connects 42 million customers with local experiences — restaurants, events, wellness, and travel — and the million-plus merchants who deliver them. Our mission is to get people offline and into the real world at prices that make it possible. We're an AI-native company in the middle of a platform transformation, moving from a deals marketplace to an experience discovery platform that works for customers and merchants at the same time.
We are now looking for AI Builder - Full Stack to join our team.
Groupon's internal teams are building AI agents to automate operations, but every team is solving the same infrastructure problems in isolation — no shared platform, no shared patterns. This role builds the foundation: a proprietary agent creation layer that lets engineers across the organisation ship autonomous AI solutions without starting from zero. When this hire does their job well, agent development time across Groupon drops from weeks to days and the company moves faster on every initiative that depends on AI.
Who you'll work with
Report to Daniel Lledó. A team of [2] engineers working on foundational AI infrastructure. This team ships experimental platform code into production fast — if you need fully scoped requirements before starting, this environment will frustrate you.
What you'll be doing
- Building and expanding the proprietary agent platform so that non-ML engineers across Groupon can ship AI solutions without reinventing core infrastructure
- Engineering reasoning flows and integration layers that connect agent systems to production services, with your name on the reliability of every downstream consumer
- Designing failure-handling and redundancy patterns so agents degrade gracefully rather than failing silently under real conditions
- Building the tools — intent retrieval, context management, API routing — that every future agent in the company depends on
- Owning code quality in a fast-moving codebase, catching the patterns that create future incidents before they reach the teams building on top of you
- Embedding AI-native development tooling (Claude Code, Cursor) into daily workflows as standard practice, not an experiment
What success looks like
- Day 30: Environment set up, first production bug fixed, first PR merged into the agent platform. You understand the existing architecture well enough to explain its tradeoffs to a new hire.
- Day 60: First independent feature shipped — an agent building block that at least one other team is already using. You've identified one structural risk in the platform and proposed a fix.
- Day 90: Operating without supervision. The platform is handling measurably more agent deployments than when you joined, and you own at least one cross-cutting concern end-to-end.
How we operate
- Extreme Ownership: The platform you build becomes the dependency every AI team relies on. Your responsibility doesn't end at the PR.
- Speed Over Comfort: The agent space is moving fast. Working drafts shipped and iterated beat polished specs that arrive late.
- Impact Obsessed: The measure of success is how many teams are shipping AI solutions faster because of the infrastructure you built.
About Groupon
Groupon is an AI-First Company. We’re committed to building smarter, faster, and more innovative ways of working—and AI plays a key role in how we get there. We encourage candidates to leverage AI tools during the hiring process where it adds value, and we’re always keen to hear how technology improves the way you work. If you’re passionate about AI or curious to explore how it can elevate your role—you’ll be right at home here.
Groupon’s purpose is to build strong communities through thriving small businesses. To learn more about the world’s largest local e-commerce marketplace, click here. You can also find out more about us in the latest Groupon news as well as learning about our DEI approach.
Groupon connects 42 million customers with local experiences — restaurants, events, wellness, and travel — and the million-plus merchants who deliver them. Our mission is to get people offline and into the real world at prices that make it possible. We're an AI-native company in the middle of a platform transformation, moving from a deals marketplace to an experience discovery platform that works for customers and merchants at the same time.
We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact.
We encourage candidates to leverage AI tools during the hiring process where it adds value, and we’re always keen to hear how technology improves the way you work. If you’re passionate about AI or curious to explore how it can elevate your role—you’ll be right at home here.
What this role demands
- Production TypeScript and Node.js across backend and frontend (Express, React, Next.js, SQL) — shown through shipped software, not side projects
- Hands-on experience with Chain of Thought reasoning, agent architectures, and RAG — not theoretical familiarity
- Docker, Kubernetes, and Linux in production — you've debugged real incidents, not just run tutorials
- AI-first working practice: Claude Code or Cursor is already part of how you work, not something you're open to trying
- Ability to ship into a shared platform used by multiple teams — you think about downstream impact before merging
