GTM Engineer

Responsibilities

• Architect the GTM Tech Stack: Build an AI native tech stack with seamless integrations.
• Centralize Data: Build a cohesive, automated engine that centralizes data in CRM and eventually data warehouse (Salesforce, Hubspot, Snowflake, Clay, Claude Cowork).
• Own Data Integrity: Build and maintain the data flows, enrichment logic, and sync architecture that keep our systems accurate, deduped, and trustworthy end-to-end.
• Turn Strategy into Systems: Partner with leadership to translate GTM strategy into automated playbooks, dynamic scoring models, and signal-based workflows that drive measurable revenue outcomes.
• Lead CPQ System Design: Lead system design for Salesforce CPQ, including product catalog architecture, pricing and discount rules, quote templates, and approval workflows.
• Optimize Conversions: Optimize quote-to-order conversion ensuring accurate data flow into downstream billing and ERP systems.
• Implement Governance: Implement governance on pricing, discounting, and quote approval thresholds to maintain margin and compliance integrity.
• Improve Deal Velocity: Improve deal velocity by streamlining approvals, leveraging Salesforce CPQ (Revenue Cloud).
• Integrate CLM Tools: Integrate CLM (e.g., Ironclad, Conga, or DocuSign CLM) with Salesforce to automate quote-to-contract and contract-to-order workflows.
• Automate Bottlenecks: Identify repetitive work across the GTM org - account research, CRM hygiene, post-call follow-ups - and replace it with intelligent automation using APIs, webhooks, and AI agents.

Requirements

• 3–5+ years of experience operating in a Growth, GTM Engineer, or Revenue Operations role. Open to candidates that have a technical background that have worked with a GTM team in other capacities.
• Builder and systems thinker: You want to build moonshot ideas, not just toggle settings. You see the GTM stack as an interconnected machine, not a collection of point solutions.
• Direct experience with Salesforce — you know the data model, you've built on it, and you're comfortable owning CRM-level changes.
• GTM-fluent: You understand the GTM funnel - not just the data model, but the logic behind every stage. You know what actually converts pipeline because you've worked in or alongside GTM teams.
• Strong working knowledge of quoting tool configurations and CLM (pricing rules, product bundles, approval chains).
• Constant iteration: Be a Kaizen methodology champion by building, shipping and iterating fast. You thrive in ambiguity, operate with high ownership, and move fast without waiting for perfect requirements. But you know when to slow down and ensure you’re shipping the highest quality work possible.
• Comfortable working with APIs, webhooks, data integrations and can navigate technical documentation without hand-holding.

Preferred Qualifications

• Prior experience at a fast-moving B2B SaaS / AI startup or strong familiarity with the AI tooling ecosystem.
• Hands-on experience with Salesforce and Clay, bonus points for building data warehouses.
• Prior quoting tool and CLM implementation experience.
• Experience designing enrichment and outbounding process and managing complex data sourcing across multiple providers.
• Experience centralizing selling signals from multiple data sources into a single location.
• Technical familiarity with GTM & automation tools (Salesforce, HubSpot, CPQ, Ironclad, Clay, Gong, Apollo, Clari, APIs, webhooks, etc.).

Compensation

The US base salary range for this full-time position is: $160K-190K + equity + benefits.