Go-to-market Engineer I, Smb

Apollo.io Apollo.io · Enterprise · United States · Sales

Go-To-Market Engineer role focused on building AI-driven systems and automation for customer outreach, adoption, and revenue growth within the SMB segment. The role involves designing and executing GTM campaigns, leveraging usage data for interventions, and advising customers on strategy, with a strong emphasis on AI-native approaches and systems thinking.

What you'd actually do

  1. Own customer outcomes post-sale: GRR (95%+), NRR, product adoption, and credit consumption growth across your Managed book of accounts.
  2. Design and execute GTM campaigns at scale: Build layered, signal-based outbound workflows — from ICP definition and enrichment logic through to messaging, sequencing, and feedback loops — that drive measurable pipeline and expansion.
  3. Turn usage data into interventions: Use product telemetry (Apollo, Vitally, Hex) and behavioral signals to identify adoption gaps, expansion triggers, and churn risk across your book — and act on them before customers ask you to.
  4. Configure Apollo to power AI-driven workflows: Build agentic systems — with appropriate QA and guardrails — that automate and optimize outreach, credit consumption, and seat expansion plays for your accounts.
  5. Advise customers on GTM strategy: Partner with RevOps, Sales, and Marketing contacts to align Apollo to their pipeline and revenue objectives — and prove ROI with measurable lift.

Skills

Required

  • 4+ years in RevOps, Growth, Sales Development, or GTM consulting
  • track record of owning campaign performance and customer outcomes
  • designing GTM campaigns, workflows, and systems agentically
  • built with tools beyond foundational models — MCP, n8n, Clay, Bolt, or Lovable
  • understand how to apply QA and guardrails to ensure systems perform reliably
  • systems thinker
  • Data-fluent
  • Execution-obsessed
  • Customer-facing and outcome-oriented

Nice to have

  • AI-native
  • systems thinker
  • Data-fluent
  • Execution-obsessed
  • Customer-facing and outcome-oriented

What the JD emphasized

  • AI-native
  • agentic systems
  • QA and guardrails

Other signals

  • AI-native systems builder
  • designing and deploying scalable intervention playbooks
  • configure Apollo to power AI-driven workflows
  • build agentic systems