GTM Engineer

Responsibilities

• Build and operate the automated systems powering the revenue engine, including AI agents and workflows for prospecting, enrichment, scheduling, CRM hygiene, and post-call follow-ups.
• Integrate Salesforce, Clay, Apollo, and other tools into a cohesive GTM system with reliable data flows, enrichment logic, synchronization, routing, and deduplication.
• Own Salesforce objects, fields, tables, flows, automations, validation rules, and integrations.
• Build outbound systems covering intent detection, account enrichment, AI-personalized touchpoints, human review, and CRM synchronization.
• Automate marketing and customer success workflows, including lifecycle marketing, lead scoring, churn-risk alerts, onboarding sequences, and customer health monitoring.
• Partner with sales, marketing, and customer success leadership to turn GTM strategy into automated playbooks, scoring models, and signal-driven workflows.
• Own data quality and governance through validation rules, deduplication logic, and dependable data structures.
• Build observability, monitoring, and debugging into systems; document shipped workflows and integrations.
• Surface product friction and propose features based on internal GTM automation experience.

Requirements

• 3+ years of experience in GTM Engineering, Growth Engineering, Revenue Operations, technical RevOps, or an adjacent technical role.
• Experience working with APIs, webhooks, data integrations, SQL, scripting, and data manipulation.
• Fluency with sales funnels, CRM data models, Salesforce or HubSpot, and enrichment ecosystems such as Clay, Apollo, and 6sense.
• Familiarity with LinkedIn Sales Navigator, Unify or similar sequencers, HeyReach, PhantomBuster, and related GTM tooling.
• Understanding of first-touch, second-touch, last-touch, view-through, and multi-touch attribution.
• Experience with PostHog, Google Analytics 4, Google Tag Manager, Meta Pixel, server-side conversion events, and revenue reporting.
• Experience shipping internal tools, automation pipelines, or data workflows that improved team output.
• Experience building with LLMs, prompt engineering, or AI agents.
• Ability to determine when to use AI decision-making versus deterministic workflows.
• High ownership and comfort operating in ambiguous, early-stage environments.

Nice-to-haves

• Familiarity with Gumloop, Claude, Cursor, OpenAI, or equivalent AI-native tools.
• Computer science degree or equivalent technical background.
• Open-source contributions or side projects related to automation, agents, or data pipelines.
• Familiarity with LinkedIn Ads, Google Ads, and Meta Ads.
• Experience building account-based marketing campaigns from scratch.
• Experience shipping production LLM applications or background in analytics or data engineering.

Compensation and benefits

• $150,000–$250,000 salary and meaningful equity.
• 24 days of paid time off for San Francisco employees.
• $350/month wellness benefit.
• 15 days of temporary remote-work flexibility per year.
• 401(k) match up to 6%.