Description: Sumble helps go-to-market teams win with deep account intelligence and signals that other data vendors simply can't provide. We map every account, person, and job post globally to uncover insights that were previously impossible to gather. For example, we can identify every company in the US currently running a data migration project involving Databricks, while pinpointing the exact team and person leading the initiative. Backed by a $40M Series A (Coatue, Canaan), we are a team of 20+ engineers and sales leaders from Google, Meta, Snowflake, and Rippling. We've scaled to millions in revenue without a marketing department. Now, we're building the growth infrastructure to match the product. About the Role We're looking for a GTM Engineer to be the technical backbone of our marketing and revenue operations. You'll sit at the intersection of marketing, sales, and engineering. You will build the systems, automations, and data pipelines that turn Sumble's go-to-market motion from manual effort into a scalable machine. This isn't a traditional "marketing ops" role. You'll for sure be writing code. In fact, the Sumble app is structured from the ground up in one monorepo, which lends itself very well for coding. You'll build automations that route Sumble's own signal data into outbound sequences, creative dashboards to create tooling for other GTM teams, build reporting dashboards. You will sit on top of the canonical data set of companies, people, and initiatives happening in the world, and you will think of creative ways to deploy it. If you've ever wished you could combine the builder mindset of a software engineer with the strategic leverage of a growth marketer, this is the role. Our Team: We are a team of around 16 engineers, data scientists, and designers with experience working at companies such as Google, Stack Overflow, Kaggle and Meta. We also have a 3-person sales team from companies like 11x, Snowflake, Confluent and Opendoor. Our growth team is from Rippling. We're fully remote in US time zones. What You'll Do - Build the GTM Stack: Own the selection, implementation, and integration of our marketing and sales tools (CRM, enrichment, sequencing, attribution, analytics). Make them talk to each other. - Signal-to-Pipeline Automations: Use Sumble's own data to build automated workflows — e.g., when a target account posts a job matching a buying signal, automatically enrich, score, and route that account to the right rep with context. - Attribution & Analytics: Instrument end-to-end marketing attribution so we know exactly what's driving pipeline. Build dashboards and reporting that the marketing and sales teams actually use. - Campaign Infrastructure: Build the technical scaffolding for marketing campaigns — landing pages, lead capture, nurture sequences, A/B testing frameworks, and personalization logic. - Internal Tooling: Prototype lightweight internal tools (scripts, dashboards, Slack bots) that make the revenue team faster. Think: "competitive intel alerts" or "account research auto-briefs" powered by Sumble data. - Data Hygiene & Enrichment: Own the integrity of our CRM and marketing data. Build enrichment pipelines, deduplication logic, and lifecycle stage definitions. - Experimentation: Run growth experiments across channels — test new outbound sequences, landing page variants, and lead-scoring models. Measure everything. Who You Are - A Builder Who Thinks in Systems: You see a manual process and immediately think about how to automate it. You're happiest when you're shipping something that makes a team measurably faster. - Technical and Business-Fluent: You can write vibe-coded Python, work with APIs, deploy scripts, and are curious to learn any latest tech trends that helps you generate pipeline. - Comfortable in Ambiguity: We're building this function from scratch. You'll need to prioritize ruthlessly, make decisions with incomplete information, and iterate fast. - Curious About GTM: You follow the modern GTM/RevOps conversation. You have very strong opinions on tools like Clay, Apollo, HubSpot, Salesforce, and you're excited about the "GTM engineer" movement. - Detail-Oriented but Fast: You care about clean data and reliable systems, but you don't over-engineer. You ship v1 quickly and improve from there.

• Design, build, and maintain backend services primarily in Java • Contribute to frontend development using TypeScript and modern frameworks • Own features end-to-end, from architecture to production deployment • Troubleshoot and resolve production bugs quickly, especially during U.S. business hours • Collaborate closely with Product and Engineering leadership across Europe and the U.S. • Participate in code reviews and maintain high engineering standards • Contribute to architectural discussions and technical decision-making • Work independently in a small team of 4 engineers

• Design and build full-stack applications that power AI-driven workflows for enterprise users. • Oversee and review the work of other engineers, ensuring high-quality, production-ready code. • Provide technical guidance, architectural direction, and hands-on support where needed. • Develop high-performance front-end interfaces for AI agent control, monitoring, and visualization. • Build scalable backend services that support real-time AI interactions, knowledge retrieval, and automation. • Work closely with AI researchers and ML engineers to integrate LLMs, RAG, and automation into production-ready systems. • Establish engineering best practices across testing, deployment, and performance optimization. • Continuously iterate and refine AI-driven products, balancing speed with robustness.

• Lead the design, development, and delivery of high-scale, data-driven applications across the full stack • Mentor and guide engineers through code reviews, design discussions, and pairing sessions, raising the technical bar across the team • Champion engineering best practices, driving improvements in scalability, reliability, observability, and security • Collaborate closely with product managers and cross-functional teammates to translate business needs into elegant, well-architected solutions • Influence system architecture decisions and take the lead on high-impact technical initiatives • Serve as a steward of good data practices, ensuring privacy, security, and accuracy of critical datasets • Act as a change agent within the engineering organization—introducing new tools, workflows, and approaches that improve how we deliver software • Contribute thought leadership and technical expertise to support our long-term product and technology strategy