Gtm Engineer, AI & Automation

ClickHouse ClickHouse · Data AI · United States · Go-To-Market

This role focuses on building and shipping AI-powered automation systems and agents to enhance the go-to-market (GTM) motion for ClickHouse. The engineer will design, implement, and own end-to-end solutions that automate repetitive tasks for sales, solutions architecture, and marketing teams, instrument the customer lifecycle with data signals, and establish standards and guardrails for AI usage in GTM. The role requires strong Python/TypeScript/JavaScript skills, experience with LLM APIs, agent frameworks, RAG, and production deployment with monitoring and evals.

What you'd actually do

  1. 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.
  2. Build agents and workflows that run reliably at scale and take repetitive work off Sales, Solutions Architecture, and Marketing.
  3. 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.
  4. Partner with the field to find where AI and automation create real gains, and turn those opportunities into systems people actually use.
  5. 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.

Skills

Required

  • 5+ years building automation and tooling in a GTM, RevOps, or growth engineering context
  • Production experience with the GTM stack: Salesforce, Gong and Gong Engage
  • 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
  • Strong data-activation skills: SQL, APIs, and integrations, transformation with dbt
  • A builder who ships
  • Owner-operator mindset
  • Judgment about where AI and automation help and where they create risk

Nice to have

  • Familiarity with usage-based or consumption-based business models
  • Bachelor's degree in engineering
  • master's degree

What the JD emphasized

  • systems you have shipped and run in production
  • shipped and operated these in production at real scale
  • shipped and run in production
  • runs reliably and moves a real number
  • own it, you run it, you fix it when it breaks, and you keep making it better

Other signals

  • design, build, and ship AI and automation across the GTM motion
  • Build agents and workflows that run reliably at scale
  • Instrument the customer lifecycle
  • Own what you build end-to-end
  • Set the standards and guardrails for AI in GTM