Head of GTM Engineering & Systems

What You'll Own

GTM Tech Stack and AI Foundations

• Own every tool the GTM organization runs on: Salesforce architecture, enrichment layer (Clay, Harmonic, Sumble), routing (LeanData), engagement (Gong, Lemlist, Granola), and the integrations between them.
• Make architectural decisions that compound as the GTM team scales from ~50 to 300+ members.

Quoting and Lead-to-Revenue Architecture (0 to 1)

• Build a durable quoting and lead-to-revenue architecture from scratch (native Salesforce CPQ, purpose-built tool, or custom solution).
• Enable AEs to take a deal from pricing to signed order form without RevOps bottlenecks (replacing Slack approvals, Google Docs order forms, and fragile billing handoffs).

Agentic Workflows for GTM Teams

• Build AI-assisted workflows for BDRs, AEs, SAs, sales managers, and RevOps: account research, rep-facing deal intelligence, automated pipeline hygiene, manager insights.
• Create workflows the team can't imagine working without.

Build and Scale the GTM Engineering Team

• Grow the team from two strong engineers: define hiring profiles, set technical standards, build career paths, and maintain a culture of high-quality, fast-shipping work.

Minimum Qualifications

• 10+ years in GTM Engineering, Revenue Operations, or Sales Operations at B2B companies (Consumption business model experience strongly desired).
• 5+ years of people management experience.
• Deep Salesforce architecture experience: data model, process automation, integrations, governance; proficient with modern CLI/MCP setups.
• Track record of driving real-world sales rep productivity enhancements measured in revenue impact.
• Experience building or rebuilding a quoting or CPQ workflow at meaningful scale.
• Experience leading a team and setting technical direction (beyond just managing execution).
• Track record of building automation that sales reps actually use.

Preferred Qualifications

• Shipped agentic or AI-native GTM workflows in production (not pilots).
• Experience scaling GTM systems through a high-growth phase (Series B to D).
• Familiarity with usage-based or consumption pricing models.
• Experience at an AI/ML infrastructure, developer tools, or API-first company.

Compensation

Total compensation includes meaningful equity in a fast-growing startup, competitive salary, and comprehensive benefits. Base Pay Range (Plus Equity): $250,000–$270,000 USD.