GTM Engineer - Revenue Programs

• 3+ years of experience in Revenue/Sales Operations, GTM Engineering, or a technical RevOps role within a B2B SaaS company.
• Deep technical knowledge in Clay, automation tools like Make (or comparable no-code/low-code automation platforms such as Zapier or n8n) and Salesforce.
• Hands-on familiarity with the modern GTM stack: SalesLoft (or Outreach), ZoomInfo, Qualified, Snowflake, and sales engagement platforms.
• Demonstrated experience with AI tools and prompt engineering
• Strong analytical instincts, systems thinking and solution orientation
• Exceptional collaboration and stakeholder management skills as well as communication skills, with the ability to clearly articulate complex technical trade-offs and recommendations to senior leadership.

• Experience building with Claude, OpenAI, or other LLM APIs
• Familiarity with MCP (Model Context Protocol) or agentic workflow tooling.
• Experience with SalesLoft admin
• Background in or exposure to B2B sales - understanding what good discovery, deal progression, and coaching look like from the seller's perspective makes this role significantly more impactful.

Make is the platform to manage all your automations and AI agents in one visual landscape - for teams driving business impact without relying on developers. Part of Celonis, a global leader in process intelligence recognized on the Forbes Cloud 100 for seven consecutive years, we're headquartered in Prague, Czechia, with hubs in Madrid, Munich, Raleigh, and Pristina, and teams across the UK, France, India, and the Netherlands, among other locations.

We are seeking a Revenue Programs GTM Engineer to work as the technical backbone of our Revenue Programs & Projects team. This is a hands-on, high-impact role for someone who thinks in systems, builds in Clay and Make, and gets energized by connecting technical work directly to sales outcomes.

You will own the AI and automation infrastructure that powers our entire GTM motion - from end-to-end data enrichment pipelines and AI-driven outreach personalization to sales coaching agents, forecasting tools, and the internal toolbox that lets the Revenue Programs team ship faster. Unlike roles focused solely on data or process, you will be both the architect and the builder: designing systems that work at scale, then executing them with precision.

This role is for someone who takes full ownership of their initiatives and measures success not by what was launched, but by what was adopted and what moved the business.

Full ownership of the data enrichment lifecycle within Salesforce and Snowflake. You will architect and maintain end-to-end pipelines, utilizing Clay and AI, while managing campaign operations, credit budgeting, and re-enrichment logic. A critical component involves partnering with cross-functional teams like RevOps and Data to audit data accuracy, resolve field-level conflicts, and ensure Salesforce remains reliable for reporting and analytics.

Responsibility for engineering the team's AI ecosystem, ranging from building sales-specific tools like call scorecards and forecasting automations to managing the personalization infrastructure that drives outreach. A major focus is maintaining the "Revenue Programs MCP Toolbox", a library of reusable AI tools and Make scenarios, to accelerate the wider team's delivery. You will also oversee the critical context infrastructure (version control and governance) that powers these agents and serve as the technical lead across all revenue programs.

Responsibility for driving sales efficiency by ensuring the adoption of your AI tools, leading their implementation with sales leadership, automating repetitive tasks, and continuously monitoring their performance using data.

Lead high-impact, cross-functional initiatives from concept to adoption, focusing on tangible business outcomes rather than just delivery. You will provide technical support to program managers, proactively manage risks and architectural blockers for leadership, and adhere to a quarterly requirement to build automations for both personal and organizational efficiency