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Upside is transforming brick-and-mortar commerce by bringing online retail sophistication—profit measurement, attribution, incrementality—to physical retail. The company helps millions of consumers earn 2-3x more cashback and hundreds of thousands of retailers acquire profitable customers. Billions in commerce flow through Upside annually.
You'll be the first engineering hire on a new internal platform effort within Revenue Operations. This is a zero-to-one, AI-native system designed to orchestrate work for go-to-market teams, replacing cumbersome legacy tooling with agentic automation.
As a forward deployed engineer, you'll be embedded directly with revenue teams—merchants acquisition, partner success, revenue drivers—understanding their workflows firsthand and building systems that meaningfully change how they work. You'll report to the Sr. Director of Revenue Operations and own technical direction: architecture decisions, tool selection, and foundational patterns.
Key responsibilities include building the first version of an AI-native platform for GTM teams; embedding with revenue teams to learn workflows and ship systems that unlock business outcomes; owning technical architecture and direction; moving from prototype to production rapidly while iterating as AI capabilities evolve; anchoring work to measurable business impact; collaborating with security and infrastructure partners; and documenting decisions for future team members.
You'll need roughly 8 years of staff-level engineering experience or equivalent depth through another path, with a track record of owning systems end-to-end. You should have real production experience with LLMs and AI APIs—prompt design, output evaluation, reliability iteration—and fluency with AI-assisted development tools as part of your workflow. Strong technical judgment, ability to refactor and pivot as requirements shift, and genuine curiosity about business operations are essential. You'll work with high independence and ambiguity while bringing stakeholders along.
The role is language-agnostic; current prototypes use React, TypeScript, and Python, but you'll have input into the tech stack. Nice-to-haves include CRM/revenue data model understanding (Salesforce, HubSpot), early-stage or founding engineer experience, familiarity with RAG and vector databases, marketplace or high-growth background, and modern data platform experience (Snowflake).
