Revenue Operations Engineer (AI & Automation) in Berlin

• As a Senior Revenue Operations Engineeer you anchor the build end of Revenue Operations - our internal product team whose customers are the GTM functions: Sales, CS, Marketing, and Finance
• You build the AI, automation, and data foundations that make these teams faster, smarter, and more scalable, owning the end-to-end delivery of internal tools, integrations, and AI-powered workflows - from problem framing and architecture through launch, adoption, and measurable business impact
• Building: AI, Automation & Systems (ca. 65%):
• You identify and productionize high-leverage AI use cases across Sales, Customer Success, Marketing, and Finance, including LLM integrations, workflow design, evaluation, guardrails, and monitoring
• You design and build lightweight internal applications and interfaces that remove recurring manual work, improve decision-making, and are simple for teams to adopt
• You build end-to-end workflows using Make, n8n, and custom logic, including business rules, system handoffs, error handling, alerts, and ongoing monitoring
• You create clean, maintainable data flows between HubSpot, the data warehouse, billing, support, and other GTM tools using APIs, webhooks, enrichment pipelines, and data activation
• You work deeply within HubSpot’s objects, properties, workflows, and integration layer to support complex use cases without creating fragile or unnecessarily complicated architecture
• Discovery & Solution Design (ca. 15%):
• You translate scoped or ambiguous business problems into clear technical solutions, define success metrics, and choose the simplest approach that can deliver meaningful impact
• Deployment, Adoption & Documentation (ca. 20%):
• You test, document, deploy, and iterate on solutions with end users so they remain secure, maintainable, reliable, and useful after launch
• Stakeholders:
• RevOps: Your peers and manager to collaborate on projects and daily initiatives
• Engineering team: Coordinate with engineers for projects that may require product know how and integration across the engineering tool stack GTM teams as and when required

Benefits

• Competitive compensation package that includes salary, benefits, and stock options of Superchat. We want everybody to be a true owner in Superchat
• 26 days of paid vacation + 2 days off for Christmas and New Year’s Eve (because we love what we do, but we also love vacation!)
• Regular company and team events like pizza & bear evenings, sport activities, Christmas parties, and more!
• Annual personal development budget of €500 for conferences, courses, books, career coach, etc
• An inclusive and exciting start-up environment culture that offers accelerated career and personal growth
• Beautiful office in the heart of Berlin (Hackescher Markt) equipped with ergonomic chairs, height adjustable desks, free snacks, beverages and overall good vibes

You bring 3+ years of hands-on experience in RevOps, GTM Engineering, SalesOps, Business Systems, or a comparable B2B SaaS role, and can show production systems you personally builtYou’ve integrated LLMs into real workflows or tools through APIs and understand how to move beyond prompting into reliable, production-ready use casesYou start with the user and business problem, map the relevant process and data dependencies, and choose the simplest scalable solution rather than defaulting to a particular toolYou’re comfortable working with APIs, webhooks, JSON, authentication, data models, and the movement of data between multiple systemsYou can take a project from discovery and architecture through building, testing, rollout, documentation, monitoring, and ongoing improvementYou ship quickly without treating reliability as optional, including appropriate testing, error handling, security, observability, and documentationYou are fluent in written and spoken English; German is a plusYou can explain technical decisions simply, manage trade-offs, work through ambiguity, and collaborate effectively with both technical and non-technical stakeholdersYou connect technical work to measurable outcomes such as pipeline, productivity, data quality, speed, cost, or customer experienceYou actively experiment with new technologies, learn through building, and share useful findings without chasing novelty for its own sake