Builder instinct, not advisor instinct
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You have designed, built, and shipped AI-enabled workflows that are still running without you. Not proofs of concept — production systems with measurable outcomes.
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Hands-on fluency with AI automation platforms — Clay, Zapier, Make, Workato, n8n, or equivalent — integrated with CRM, marketing automation, and customer success tools beyond surface-level configuration.
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Working knowledge of prompt engineering, agent-based workflows, AI orchestration, and emerging approaches like Model Context Protocol (MCP) — enough to evaluate, build, and govern with confidence.
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You don’t need to be a deep engineer to succeed here. You manage tools effectively, understand APIs at a working level, know when to iterate versus when to escalate, and collaborate with technical colleagues when the problem demands it. Scripting ability in Python or JavaScript is a genuine bonus — vibe-code welcome.
Revenue fluency from lived GTM experience
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Real time spent inside a revenue organization — RevOps, Sales Ops, Marketing Ops, Enablement, or GTM Operations — with a working understanding of how deals move, customers expand, and where friction lives.
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You know what a seller needs before a discovery call, what a CSM needs to identify churn risk early, and what a marketer needs to prioritize the right accounts. You have built things that delivered those outcomes.
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Able to translate between business problems and technical requirements without losing either side of the conversation.
Data-driven and analytically sharp
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Experience using data, dashboards, and reporting to identify opportunities, measure impact, and drive decisions — not just report on activity.
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Comfortable working with SQL, BI platforms (Power BI, Tableau, or equivalent), and data infrastructure such as Snowflake.
Cross-functional and self-directed
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Track record of driving adoption across Sales, Marketing, CS, IT, and Leadership without formal authority — influencing through outcomes, not authority.
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Operates independently, prioritizes competing demands effectively, and delivers in fast-paced, high-growth environments where the playbook is still being written.
You likely come from one of these backgrounds:
Ex-RevOps or GTM Ops builder who went deep on AI tooling and automation and realized the biggest leverage is in building systems, not maintaining them. You have seen the inefficiencies from the inside, you know exactly where the friction lives, and you are ready to eliminate it permanently.
Technical Marketing or Sales Ops specialist from a B2B SaaS company who has built end-to-end workflows across HubSpot, Gong, Clay, and related platforms — and is ready to own that work at a higher level of strategic impact inside a company that is serious about AI.
Early-stage GTM engineer at a SaaS company who built AI-powered prospecting, scoring, or CS automation in a fast-moving environment with no playbook — and thrived. You wrote the playbook. Now you want a bigger stage.
What all three share: you have shipped things that are running in production, you can point to the outcomes, and you are more energized by the next build than the last one. You are comfortable being scrappy, learning as you go, and finding the solution through experimentation rather than waiting for a perfect brief.