About the role
About
the role Rippling's GTM engine is uniquely powerful because we have a massive total addressable market (everyone needs payroll), support thousands of sellers across 30+ products, and sit on a rich data foundation that most companies can only dream of. The GTM Engineering team builds cutting-edge AI agents and automated systems that turn that data into pipeline at scale. We are looking for a GTM Engineer to join our GTM Engineering team and build the application layer on top of our growth engineering infrastructure. You'll leverage solved infrastructure problems (vector databases, agent memory, scoring models) and turn them into prospect-facing agents and automated workflows that marketing and growth teams use every day. You will be responsible for building and deploying AI agents across marketing execution, developing and scaling agentic workflows for programmatic outbound, building and maintaining enrichment and scoring infrastructure, and running structured experiments to find what delivers alpha for pipeline generation. We are looking for someone technical enough to build agents from scratch and business-savvy enough to know which ones are worth building. You don't need prior experience in growth or marketing, but you should have a CS background and past experience building with LLMs. You'll have real responsibility over a critical part of the growth infrastructure, and you will learn how a billion-dollar company actually grows. This is a perfect role for anyone who loves building AI systems, growing revenue, and getting things done. You should apply if you want to be at the cutting edge of go-to-market. What you will do Design and ship AI agents that automate marketing execution — SEM optimization, paid social content, programmatic outbound, and more Build prospect-facing agentic workflows that operate at scale across email, Meta, and LinkedIn Architect prompt systems, orchestration logic, and evaluation frameworks to ensure agent reliability Build V0s of new growth initiatives using AI coding tools (Claude Code, Cursor), prove them with stakeholders, and partner with growth engineering to productionize Apply infrastructure built by growth engineering (vector databases, agent memory, scoring models) to create applications the marketing and growth teams use daily Build and maintain enrichment pipelines, lead scoring systems, and routing logic that power the marketing and growth engine Find, test, and scale new intent signals and engagement triggers that deliver alpha for pipeline generation Run structured experiments on agent behaviors, signals, and automation approaches — ship fast, measure, iterate or kill Track the performance and ROI of what you build; use data to inform what gets scaled vs. sunset What you will need Track record of building and shipping AI-powered or automated systems in a professional role, as a founder, or through substantial side projects CS degree or equivalent technical background. You understand concurrency trade-offs, system architecture, and can reason about why something is slow and how to fix it. Business-savvy with GTM intuition. You understand how marketing, growth, and pipeline generation work, and you have opinions on what good outbound looks like. Hands-on experience building with LLMs: prompt engineering, agent orchestration, evaluation loops. You've built at least one agent, even as a side project. AI-native. You stay at the frontier of new tools, frameworks, and agent architectures, and you bring ideas back to
