Growth Engineer

Harvey Harvey · AI Frontier · San Francisco, CA · Marketing

Growth Engineer role focused on implementing AI and automation use cases to improve marketing and demand generation velocity for a legal AI company. This role involves building and maintaining AI workflows, designing automation, managing experimentation infrastructure, and collaborating with marketing teams to translate needs into technical solutions.

What you'd actually do

  1. Own the identification, scoping, and implementation of AI and automation use cases that improve demand generation velocity, campaign operations, pipeline conversion and more.
  2. Build and maintain AI workflows from automated content creation to intelligent audience targeting and personalization at scale.
  3. Design and deploy automation workflows (e.g., Claude, Clay, n8n, or equivalent) that eliminate manual work across the demand gen stack, integrating with Marketo, Salesforce, web CMS, and digital platforms.
  4. Build and run experimentation infrastructure: A/B tests, landing pages, and conversion-flow changes, directly on [harvey.ai](http://harvey.ai) and campaign surfaces, not just backend automation.
  5. Continuously evaluate emerging AI capabilities, including new models, agent frameworks, and MCP integrations, and prototype applications that give Harvey's marketing team a competitive edge.

Skills

Required

  • 4+ years of experience in growth engineering, marketing engineering, GTM engineering, or a technical role within a marketing/growth function at a B2B SaaS company.
  • Hands-on experience building _with_ AI — you use tools like Claude Code, Cursor, or equivalent as part of your daily workflow, not just as something you build on top of.
  • Experience working with LLM APIs or AI-powered tools to generate content, automate workflows, or optimize marketing performance.
  • Familiarity with marketing automation platforms (e.g., Marketo, HubSpot), CRMs (e.g., Salesforce), workflow/automation tools (e.g., Clay, n8n, Zapier, Make), and analytics/experimentation tooling (e.g., Amplitude, Mixpanel, Segment, PostHog, GA4).
  • A builder mentality, comfortable operating in ambiguity, shipping iteratively, and taking ownership of 0→1 projects.
  • Strong analytical skills with the ability to design experiments, own attribution, and translate data into decisions.
  • Cross-functional collaboration: work closely with internal teams across data science, marketing operations, performance marketing, product marketing, and sales to ensure campaign success. Drive alignment on priorities and share insights to refine strategies.

Nice to have

  • Experience with data warehouses/BI tools
  • Strong programming skills
  • Experience building on a marketing site or product surface (landing pages, onboarding, referral or lifecycle systems).
  • Background at a high-growth B2B SaaS or AI-native company.

What the JD emphasized

  • AI and automation use cases
  • AI workflows
  • automation workflows
  • experimentation infrastructure
  • AI capabilities
  • agent frameworks

Other signals

  • AI workflows
  • automation
  • LLM APIs
  • experimentation infrastructure
  • growth strategy