GTM Engineer
Build and operate the systems, data infrastructure, and applied AI workflows powering a modern GTM organization. The role requires 5+ years in a technical GTM-facing position, strong architecture and automation experience, and hands-on familiarity with AI development tools and enterprise GTM platforms.
About the job
Responsibilities
- Drive GTM systems end-to-end, including Salesforce data models, integrations, automation, CPQ, lead routing, call intelligence, data enrichment, outbound activation, and scaled support.
- Build the applied AI layer of the GTM stack, including agents and workflows that improve pipeline velocity, sales efficiency, and customer outcomes.
- Build the outbound signal engine, covering signal ingestion, enrichment, play orchestration, attribution, data modeling, and SDR-facing notifications.
- Establish GTM Engineering operating infrastructure, including deployment pipelines, branching and sandbox management, testing standards, backups, and AI development environments.
- Partner with data science on the GTM data-to-action loop: data capture, signal translation, insight generation, and workflow adoption.
- Provide technical capabilities to GTM Operations and Marketing Operations teams across systems, data, and AI tooling.
- Drive adoption and measurement as a product owner by discovering user pain, shipping solutions, managing change, measuring trust and business impact, and retiring ineffective tools.
- Build the technical foundation for organization-wide AI use, including tools, integrations, documentation, agent support, and operating standards.
- Partner with Enablement on user-facing training and AI fluency programs.
Requirements
- 5+ years in a customer-facing or GTM-facing technical role at a high-growth B2B SaaS or AI company, including revenue systems, GTM engineering, or revenue operations.
- AI embedded in current workflows, with deep experience using coding tools such as Cursor or Claude Code and enterprise agent tooling.
- Broad experience managing modern GTM technology stacks, including data enrichment, lead routing, sales engagement, call intelligence, chat, CPQ, and support.
- Strong technical background in systems design and architecture, including data models, integrations, automation, and declarative versus code-based solutions.
- Experience managing development environments and deployment pipelines.
- Willingness to work from an office 4 days per week.
Nice-to-haves
- Experience with Salesforce, Gong, Clay, and/or LeanData.
Compensation and Benefits
- Watershed has hub offices in San Francisco, New York, London, and Mexico City, and satellite offices in Denver, Sydney, Paris, and Berlin.
- Employees in offices are expected to work onsite 4 days per week.
Skills
Salesforce, CPQ, Gong, Clay, Leandata, Cursor, Claude Code, AI Agents, Data Enrichment, Lead Routing, Call Intelligence, Salesforce Automation, Deployment Pipelines, Data Modeling, Integrations
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