Founding GTM Engineer

About the role

• Plato is building an AI operating system for distribution, starting with sales for mid-market distributors who have not previously been exposed to cutting-edge AI software. The fast-growing company raised a $14.5M seed round backed by Atomico and Cherry Ventures.
• Join a small, high-conviction team of engineers and operators where decisions are made quickly and accountability matters.
• As Plato's first GTM Engineer, establish RevOps as a discipline and build the revenue engine as a product rather than a ticket queue. Your metrics are pipeline, conversion, and revenue per headcount.
• Inherit HubSpot as the source of truth, a custom-built deal-scoring app, Grain for call intelligence, and company-wide AI access. Build the underlying foundations: clean data, automated processes, rigorous forecasting, and AI-driven workflows.
• This is a team-of-one role with direct access to the founders, a mandate to change how the company works, and autonomy to decide what to build first.
• This is a full-time, on-site role in Berlin, Germany.

Responsibilities

• Establish a trustworthy data foundation through CRM hygiene, field governance, deduplication, and enrichment when records are created.
• Automate revenue processes, including lead routing, SLAs, stage criteria, and clean cross-team handoffs.
• Build the pipeline-generation stack for signal-based outbound, including ICP scoring, enrichment waterfalls, and orchestration, so the team can focus on conversations rather than list-building.
• Integrate AI into daily workflows through call-intelligence automation, research agents, and health/churn scoring.
• Build forecasting and reporting that leadership can use to steer the business weekly.
• Ensure shipped solutions are used by measuring adoption, training the team, and iterating.

Requirements

• Must-have: Hands-on experience architecting a CRM such as HubSpot from the ground up, including objects, properties, and data structures—not just administering an existing setup.
• Must-have: Practical production experience with outbound and enrichment tools such as Clay or similar platforms.
• Must-have: Experience building with AI/LLMs in production, including prompt design, agents, or AI-powered workflows.
• Must-have: Strong data rigor, including the ability to interpret funnels, identify dirty data, and quantify the impact of a fix before building it.
• Must-have: Systems thinking and an ability to sequence work and defend your reasoning under substantive pushback.
• Nice-to-have: Experience as an early GTM-Ops or RevOps hire at another startup.
• Nice-to-have: Familiarity with Grain and Sales Navigator-style outbound tooling, or similar tools.
• Nice-to-have: Comfort with unit economics, including CAC, ACV, and payback.
• Nice-to-have: Experience with mid-market, multi-stakeholder B2B deal cycles.

Benefits

• Ownership of building the RevOps function from scratch, with a real tooling budget and a mandate to change how the revenue team works from day one.
• Broad scope across data, process, automation, and AI.
• Opportunity to see your work move measurable business results within your first 90 days.
• Top-of-market compensation and meaningful equity.
• Close collaboration with the founders at a fast-growing, venture-backed AI startup.
• Weekly team lunches, company-paid dinners when working late, a sports membership, and regular team events.