Director, GTM Engineering

Location: Remote within the United States. Base salary is $225,000–$275,000 in San Francisco, New York City, and Seattle, and $200,000–$245,000 elsewhere in the U.S.

Base salary: $225,000–$275,000 in San Francisco, New York City, and Seattle; $200,000–$245,000 elsewhere in the U.S. Bonus, equity, and benefits are excluded.

Company

Provides real-time voice AI APIs for speech-to-text, text-to-speech, and production-grade voice agents through cloud, self-hosted, and on-premises software.

What you will do

• Own the GTM technology ecosystem across CRM, CPQ, forecasting, data infrastructure, integrations, automation, and internal tooling.
• Act as the technical product leader for GTM systems and the primary GTM counterpart to Engineering, translating business problems into requirements, roadmaps, and scalable solutions.
• Establish engineering standards covering security, governance, testing, observability, access controls, documentation, and safe production deployment.
• Build AI-native workflows and internal tools for pipeline management, forecasting, deal execution, renewals, reporting, and decision-making.
• Connect pipeline, bookings, contracts, product usage, customer activity, renewals, and expansion into a reliable commercial data foundation.
• Lead usage, metering, billing, forecasting, territory, quota, commission, and capacity systems while developing a small player-coach team.

Requirements

• Experience building and leading GTM Engineering, RevOps, Sales Ops, Business Systems, or a similar technical GTM function.
• Professional software engineering experience, including independently writing, reviewing, debugging, and maintaining production-quality code without relying on AI-assisted development tools.
• Demonstrated experience personally designing, coding, testing, and shipping production systems, integrations, automations, agents, or internal tools.
• Strong understanding of software architecture, APIs, security, governance, testing, observability, access controls, and production engineering practices.
• Deep hands-on experience with CRM, CPQ, APIs, integrations, workflow automation, and commercial data.
• Experience building AI-powered workflows that replace or materially reduce manual work.
• Strong product instincts and the ability to turn ambiguous business problems into buildable solutions.
• Technical credibility with Product and Engineering, strong communication with GTM leaders, and experience partnering with Data or Analytics Engineering on data modeling, governance, metadata, and shared data infrastructure.
• Strong understanding of pipeline, forecasting, quote-to-cash, and customer lifecycle data; comfortable operating as a hands-on player-coach with a small team.

Nice to have

• Experience in a usage-based or consumption-based business, especially metering and billing infrastructure.
• Experience with Salesforce, CPQ or billing platforms, SQL, and GTM data pipelines.
• Experience with AI-assisted development tools such as Claude Code and Cursor, alongside automation platforms such as n8n, Workato, or Retool.
• Experience scaling GTM systems through rapid growth or multi-product expansion.

Culture & Benefits

• Remote work within the United States.
• AI-first operating model with an expectation to actively use, experiment with, and build advanced AI tools.
• Fast-changing environment requiring experimentation, adaptability, and continuous learning.
• Base salary varies by U.S. work location and factors such as skills and experience.