GTM Engineer

Nash

. Build and operate AI agents for account research, signal qualification, message construction, routing, and reply handling .

Posted 10/30/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating AI agents for go-to-market systems, with a strong focus on integrating paid media and account-based marketing strategies. Proficient in managing CRM systems, data models, and API integrations to enhance pipeline performance and data quality.

Highest-signal resume keywords

Go-To-Market ExperienceAI Application in GTM SystemsFluency in Python or TypeScriptSalesforce Development ExperiencePaid Media Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Agent DevelopmentAPI IntegrationSQLData Quality ManagementOutbound Sequence CreationCampaign ManagementEntity ResolutionEvidence TypingMarket SegmentationAutomation

Soft Skills

Ability to Scope RequestsCommunication of Tradeoffs

Tools & Technologies

SalesforceClaude CodeCursorGTM OSCRM Systems

Industry Keywords

Account-Based MarketingPaid MediaLifecycle ProgramsPipeline ResultsCampaign Attribution

Tech Stack

Tools & technologies

PythonSQLTypeScriptGo

About the role

Key responsibilities & impact

Build and operate AI agents for account research, signal qualification, message construction, routing, and reply handling
Design, evaluate, roll out, and monitor GTM agents
Build infrastructure integrating paid media and ABM, including CRM-generated audiences, rule-based campaign management, agent engagement feedback, and spend attribution
Own the account context layer, including entity resolution, evidence typing, freshness, provenance, and market segmentation rules
Extend GTM OS, Nash's internal platform, for use by sales and marketing within existing tools
Serve as technical owner for go-to-market systems, CRM, data model, routing logic, integrations, and automations
Own sending infrastructure and deliverability, including domain strategy, warming, suppression, and sender reputation
Maintain production standards through evaluations, observability, permissions, and auditability
Measure and improve reply rates, meeting rates, pipeline, revenue, cost per account worked, agent reliability, and data quality

Requirements

What you’ll need

Go-to-market experience in outbound, paid, ABM, or lifecycle programs, including demonstrated pipeline results and systems built to run them
Production experience shipping and maintaining a service, agent, or pipeline that others depended on
Experience creating scalable outbound sequences tied to buyer changes and company offerings, with demonstrated reply rates
Paid media experience, including running budgets and building audiences
Hands-on experience applying AI to go-to-market systems, including agents, LLM-based automation, MCP-style integrations, and evaluations
Fluency in Python or TypeScript
Daily experience with Claude Code, Cursor, or equivalent, with specific opinions about tooling limitations
Experience building and debugging API integrations; understanding of authentication, rate limits, sync direction, and failure modes
Salesforce development experience, including its data model, API, and Apex, or ability to learn it quickly
SQL and warehouse concepts; ability to trace data quality issues from source to destination
Ability to scope vague requests and explain tradeoffs

Benefits

Comp & perks

Competitive compensation and opportunity for equity
Quarterly broader team on-sites to bond with teammates
Flexible paid time off
Health, dental, and vision insurance for US employees
Early-stage, well-funded startup with opportunities to directly impact the company and grow your career