About the role
About ClickHouse Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads. The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla. We’re on a mission to transform how companies use data. Come be a part of our journey! We are looking for a GTM Engineer to build the AI and automation that make ClickHouse's go-to-market motion faster, smarter, and more scalable. This is a builder role. You will design, build, and ship the systems, agents, and workflows that take manual work off
the team and put usage and customer signals to work across the lifecycle. ClickHouse runs on a consumption model, where the returns from instrumenting and automating the customer journey are large and mostly uncaptured. This role exists to capture them. As part of the Revenue Operations team, you will work directly with Sales, Solutions Architecture, Marketing, and RevOps to find the highest-value opportunities and turn them into working systems. This is an individual contributor role for someone who wants to build, own what they ship, and set the standard for how AI shows up in our go-to-market. What You'll Be Doing Design, build, and ship AI and automation across the GTM motion: prospecting and enrichment, lead routing and activation, outbound and follow-up, deal and technical sales support, and expansion and retention signals. Build agents and workflows that run reliably at scale and take repetitive work off Sales, Solutions Architecture, and Marketing. Instrument the customer lifecycle. Connect the GTM systems and data so usage and telemetry signals flow to the right place and trigger the right action automatically. Partner with the field to find where AI and automation create real gains, and turn those opportunities into systems people actually use. Own what you build end-to-end. Design it, deploy it, measure whether it moves a real number, and keep improving it. Stand up evals and monitoring so AI output stays reliable in production. Set the standards and guardrails for AI in GTM: data quality, prompt and eval discipline, human review where it matters, and controls that keep automated actions safe. Track the AI and automation tooling landscape and bring the best of it into how ClickHouse goes to market. What You Bring Along 5+ years building automation and tooling in a GTM, RevOps, or growth engineering context, with systems you have shipped and run in production. Production experience with the GTM stack: Salesforce as the system of record, Gong and Gong Engage for conversation intelligence and sequencing, and the engineering layer beneath them: Vercel, Clay, n8n, enrichment providers, and both transactional and analytical databases (Postgres and ClickHouse). You have shipped and operated these in production at real scale. Hands-on development in Python, TypeScript, and JavaScript. Fluency with modern AI tooling: LLM APIs, agent and orchestration frameworks, prompting, evals, and retrieval with embeddings and vector search. You know how to get reliable behavior out of probabilistic systems, and you use eval and observability tooling like Langfuse to keep them reliable in production. Strong data-activation skills: SQL, APIs, and integrations, transformation with dbt, and moving warehouse data into the GTM stack and back. A builder who ships. You are comfortable owning something from idea to working system, and you measure it by whether it runs reliably and moves a real number. Owner-operator mindset. You treat what you build as a system you own end-to-end: you build it, you run it, you fix it when it breaks, and you keep making it better. Judgment about where AI and automation help and where they create risk. You know when to automate a workflow fully, when to keep a human in the loop, and when to leave a process alone. Familiarity with usage-based or consumption-based business models is a plus. You understand how usage and telemetry signals drive expansion and retention. Strong written and verbal communication. Comfortable partnering across the field and explaining what your systems do and why. Bachelor's degree in engineering required. A master's degree is a plus. The typical starting salary for this role in the US is $145,000 — $195,000 USD The typical starting salary for this role in US Premium Markets is $165,000 — $225,000 USD
