Our go-to-market team wins on three things: being with the right customers, at the right moment, and bringing the right data and story to the conversation. Most of the work that keeps them from it — assembling account context, chasing signals across systems, running the recurring mechanics of the business — is work AI can now do. It isn’t being done today because our collective intelligence is fragmented: account context, market signal, product usage signal, and operating knowledge live scattered across systems and people, where AI cannot reach it.
GTM Engineering is the build discipline that closes that gap. We centralize the intelligence and build the engines that run on it, so reps spend less time assembling context and doing tedious work, and more time with customers, with a sharper case in hand when they get there. The bet is if we centralize that intelligence and build reusable engines on top of it, we inflect growth. Every time we ship, it is a power-up to the whole GTM team — new business and customer, at once.
As a GTM Engineer, you’ll sit at the intersection of business systems, data, and AI, building workflows that help Sales, Account Management, Customer Success, and RevOps move faster and operate more intelligently. You’ll own the execution of AI-driven automation across our GTM stack, using tools like Salesforce, Gainsight, Gong, Nooks, Clay, and BigQuery.This is the technical seat on the team, a senior individual contributor who treats GTM as a software problem and ships software that does the work a rep used to do. You will inherit a live portfolio of automations, own the technical end of the build, and shape a team that is being built.
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Mine the prospect base for signals and feed the pipeline: Be our Clay power user. Build enrichment waterfalls and signal-detection workflows (job changes, hiring, funding, tech-stack, and product-usage triggers) that continuously mine our prospect and account base, then score, prioritize, and route the highest-fit qualified leads straight to our account executives.
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Build AI-powered workflows and agents: Design, build, and maintain AI-driven workflows and agents using a mix of workflow tools (Salesforce Flows, Workato) and code (e.g., Python, SQL).
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Turn fuzzy problems into shipped systems: Translate ambiguous business problems and high-effort manual workflows into reliable AI-powered automation,
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Ship reliable, maintainable systems: Own your builds end-to-end. Develop the technical documentation, monitoring, and testing frameworks that keep GTM systems and AI workflows reliable, observable, and easy to adopt.
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Champion AI across GTM: Spread AI best practices across the go-to-market teams, pitch plays unprompted, and help the whole org operate more intelligently.