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GTM Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Finix Payments
Full Time position
Listed on 2026-10-16
Job specializations:
  • IT/Tech
    CRM Systems & Management, AI Engineer (Applied/Software), Business Systems & Technology Analysis, Data Engineering
Job Description & How to Apply Below
San Francisco Marketing – Marketing /Full-time /On-site About Finix Finix is building the global operating system for fintech, starting with payments. From startups to publicly traded companies, Finix processes tens of billions of dollars annually both in-store and online. Finix was founded in 2015 and is headquartered in San Francisco.

To date Finix has raised over $200M, including a $75M Series C led by Acrew Capital and Lightspeed Venture Partners and backed by American Express Ventures, Bain Capital Ventures, Homebrew, Inspired Capital, Visa, and others

About the Role We’re looking for our first Go-To-Market (GTM) Engineer to architect and operationalize the systems behind Finix’s pipeline generation engine. This is a highly cross-functional role sitting at the intersection of marketing, revenue operations, data, automation, and AI.You’ll partner closely with Marketing, Sales, Partnerships, and Operations to design scalable growth infrastructure, improve data quality, automate workflows, and build the connective tissue between our GTM systems.

You should be equally comfortable thinking strategically about pipeline generation and rolling up your sleeves inside Hub Spot, Clay, APIs, spreadsheets, and AI tooling.

This role is ideal for someone who thinks like a systems builder, operates with an owner mentality, and wants to redefine how modern fintech companies run go-to-market.

What You'll Be Doing Build GTM Infrastructure Rebuild and optimize core GTM systems and workflows across Marketing, Sales, and Partnerships that support pipeline generation and customer expansion

Own Hub Spot architecture, automation, attribution, enrichment, routing, and reporting

Design scalable lead lifecycle infrastructure and source classification systems

Create and maintain reliable GTM data pipelines across paid ads, CRM, product, and third-party tools

Build API integrations between internal systems and external vendors

Operationalize AI Across GTMDeploy AI-native workflows and agents across prospecting, enrichment, routing, qualification, and campaign operations

Build systems leveraging tools like Claude, Clay, OpenAI, and workflow orchestration platforms

Develop anomaly detection, QA checks, and automated reporting for GTM data integrity

Identify repetitive operational workflows and automate them end-to-end Partner Cross-Functionally Work closely with Marketing to improve campaign measurement, attribution, and funnel visibility

Partner with Sales and Partnerships to improve lead quality, routing, enrichment, and outbound infrastructure

Collaborate with Product and Engineering on product-led growth signals and internal tooling

Document systems, processes, and operational best practices across the GTM organization

Areas of Ownership Hub Spot  rebuild + administration

Attribution modeling

Lead/source classification

Workflow automation (Hub Spot + AI)
Ads data pipelinesCRM enrichment + deduplicationGTM reporting infrastructureAPI integrationsAI-powered prospecting workflows

Data quality monitoring + anomaly detection

Revenue systems documentation

What We're Looking For5+ years of demonstrated experience in Rev Ops, Growth Ops, Marketing Ops, Sales Ops, GTM Engineering, or related operational roles within a high-growth SaaS environment.
2+ years of engineering experience.

Strong systems thinking and technical curiosity to solve complex business problems with scalable solutions

Expert-level, hands-on experience with Hub Spot in a fast-paced environment building and maintaining workflows, audience segments, API connectors and error handling.

Proficient with AI-native GTM tooling (e.g, Claude, OpenAI, Zapier, , etc), agent frameworks (e.g. Lang Chain, CrewAI, or similar) for building multi-step AI workflows and data enrichment…
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