GTM Engineer

Together AI•San Francisco, CA

3d•$160,000 - $190,000

About The Position

We are seeking a skilled GTM Engineer to join our team. In this role, you will architect an AI-native tech stack with seamless integrations and build a cohesive, automated engine to drive measurable revenue outcomes. As a builder and systems thinker, you will play a vital role in automating processes, maintaining data integrity, and turning GTM strategy into scalable systems.

Requirements

Experience: Have 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.
Systems Thinking: Are a 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.
Salesforce Expertise: Have Direct experience with Salesforce — you know the data model, you've built on it, and you're comfortable owning CRM-level changes.
GTM Fluency: Are 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.
Quote to Cash Configurations: Strong working knowledge of quoting tool configurations and CLM (pricing rules, product bundles, approval chains).
Execution & Ownership: 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.
Technical Capability: Are technically capable: Comfortable working with APIs, webhooks, data integrations and can navigate technical documentation without hand-holding.

Nice To Haves

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.
You have technical familiarity with GTM & automation tools (Salesforce, HubSpot, CPQ, Ironclad, Clay, Gong, Apollo, Clari, APIs, webhooks, etc.).
As our ideal candidate, you will be part engineer, part hacker, with a passion for cybersecurity and a drive to protect our systems from evolving threats.

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.