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Zyphra

GTM Engineer

San FranciscoOnsite · United States
FullTime · GTM
POSTED 19 MARVERIFIED 9H AGO
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Role
235 days opentrue age
Posted 19 Mar
Pay
$161k–$239kno pay posted
Market p25–p75
$161k–$239k
SF Bay Area · n=1752 · 365d to 6 Nov
CompanyZyphra →
16open roles
Opened · 30d
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Closed · 30d
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37,620open · Software engineering
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75,147open
All tracked boards · live 10 Nov · n=37,620
PythonSQLLLMs

Zyphra is an artificial intelligence company based in San Francisco, California.

The Role

As a GTM Engineer, you will be a core builder on Zyphra's GTM team, responsible for designing, deploying, and continuously improving the AI-driven systems that power our go-to-market engine. This is not a traditional sales, sales ops or RevOps role. You will bring direct GTM domain expertise and deep, hands-on proficiency with modern AI tools and you'll use both to build infrastructure that creates lasting commercial leverage.

The best candidates for this role have done the hard work of GTM: outbound strategy, customer segmentation, messaging, business development and have also built tangible applications with AI tools. You know where the manual work hides, and you know how to engineer it away.

You’ll Work Across

Designing and deploying end-to-end AI-powered GTM workflows spanning prospecting, outreach, enrichment, qualification, and pipeline management

Building and owning the GTM tech stack with tools like Clay, n8n, HubSpot, and custom integrations, and architecting the systems that connect them

Developing and iterating customer segmentation models, ICP scoring frameworks, and signal-based targeting systems using enrichment data and AI

Rapid-prototyping new GTM motions, running structured experiments with real pipeline data, and scaling what works

Using Claude Code, Cursor, and other AI coding tools to build custom automations, scripts, and lightweight applications that accelerate GTM output

Partnering with sales, marketing, and business development to translate business needs into automated systems and measuring the revenue impact

Identifying new areas where AI tools can be applied to GTM functions, staying ahead of what's possible and experimenting before it becomes standard practice

Developing communications processes, messaging frameworks, outreach sequences, and content systems that can be personalized at scale through AI

What We're Looking For / Requirements

3–5 years of hands-on experience in B2B go-to-market roles: business development, sales operations, growth, or revenue operations, with direct exposure to customer segmentation, targeting, outbound strategy, and pipeline generation

Deep, working proficiency with AI coding tools including Claude Code and Cursor/Copilot, you build with these tools daily, not occasionally

Experience building and automating workflows with tools like n8n, Zapier, Make, or similar platforms, with the ability to design and deploy complex multi-step automations

Hands-on experience with Clay, Apollo, or equivalent data enrichment and prospecting platforms as a core part of your GTM toolset

A systems thinker who designs for scale, you see manual GTM work as an engineering problem and default to automating it

Excellent communication and collaboration skills; the ability to work across sales, marketing, product, and research teams to understand needs and ship solutions

Demonstrated ability to operate in fast-moving, ambiguous environments where the playbook doesn't exist yet

Qualifications / Additional Skills

Experience with CRM platforms (HubSpot, Salesforce) including building custom workflows, lifecycle stages, and reporting infrastructure

Comfort writing Python or SQL to build custom integrations, data pipelines, or lightweight internal tools when off-the-shelf solutions aren't enough

Familiarity with LLM prompting techniques and orchestration frameworks as applied to GTM use cases: process optimization, outreach personalization, research automation, scoring, summarization

Experience measuring and reporting on GTM automation ROI: pipeline generated, time saved, conversion improvements, CAC reduction

Comfort designing and testing messaging frameworks at the ICP, vertical, or persona level and using AI to personalize at scale

Prior experience at an early-stage or high-growth AI company, or strong familiarity with the AI tooling ecosystem

Interest in frontier AI research and the ability to translate technical product concepts into compelling commercial narratives

Source · ZyphraFirst seen 2 NovOriginal ↗