Principal AI Go-to-Market Operations Engineer

QAD

AI Go-To-Market Operations Engineer at QAD working on innovative AI solutions for revenue optimization. Collaborating across teams to leverage AI in sales, marketing, and customer success initiatives.

Posted 7/3/2026full-timeRemote • 🇲🇽 MexicoLeadWebsite

Tech Stack

Tools & technologies

JavaScriptPython

About the role

Key responsibilities & impact

Architecting an AI-first GTM ecosystem that bridges the gap between Sales, RevOps, Marketing, and Customer Success.
Design, code, and deploy custom AI integrations from scratch to connect our CRM, Sales Engagement platforms, and other technology stack components.
Build proprietary internal LLM-based tools to automate account and contact enrichment, outbound messaging for early and middle of the funnel prospects.
Develop agentic workflows that handle routine administrative tasks (e.g., CRM data, meeting summaries, and follow-up scheduling) across the revenue organization.
Partner with RevOps and Marketing Ops to audit the existing tech stack, identifying redundancies where AI can replace high-cost, low-utility third-party vendors.
Implement predictive modeling to identify high-intent pipelines and provide Sales with real-time 'Next Best Action' recommendations.
Ensure data integrity across all platforms, creating a 'single source of truth' that AI models can leverage for accurate forecasting.
Collaborate with Customer Success to build AI-driven retention loops and automated renewal triggers.
Consult with Marketing leadership on AI-driven content distribution and performance marketing automation to lower Customer Acquisition Cost (CAC).
Act as an internal consultant, training GTM teams on how to effectively 'prompt' and utilize deployed AI tools to maximize their individual output.

Requirements

What you’ll need

5+ years of experience in Marketing/Revenue Operations or GTM Engineering.
Deep understanding of the 'Leads-to-Revenue' funnel and 'Best-in-Class' SaaS ecosystems.
Ability to write and maintain production integrations — Python, JavaScript, html, or equivalent — connecting AI agents to CRM, MAP, and sequencing tools via APIs.
Deep working knowledge of the modern B2B GTM stack — specifically Salesforce (as CRM and data hub), Clay, Claude, Outreach, Gong or Chorus, etc
Proven track record of consolidating tech stacks and reducing vendor spend without sacrificing performance.
Understanding of pipeline math and unit economics: you should be able to work backward from a revenue target to pipeline required, conversion rates by stage, and the specific AI interventions that move each number.
Experience with AI agent orchestration — managing multiple AI agents working different segments or functions simultaneously, resolving conflicts, preventing duplicate outreach, and maintaining data quality in the hub (Salesforce).
Demonstrated ability to build prompt libraries, training datasets, and refinement workflows for AI agents — treating agent training as a discipline, not a one-time setup.
Strong opinions on when AI should replace human effort versus augment it — and the judgment to know that bad AI automation destroys deals faster than no automation at all.

Benefits

Comp & perks

Your health and well being are important to us at QAD. We provide programs that help you strike a healthy work-life balance.
Opportunity to join a growing business, launching into its next phase of expansion and transformation.
Collaborative culture of smart and hard-working people who support one another to get the job done.
An atmosphere of growth and opportunity, where idea-sharing is always prioritized over level or hierarchy.

ATS Keywords

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Hard Skills & Tools

PythonJavaScriptHTMLAPI IntegrationPredictive ModelingData Integrity ManagementPrompt Library DevelopmentPipeline MathUnit EconomicsAI Tool Development

Soft Skills

Consultative TrainingJudgment on AI UtilizationCollaboration with Cross-Functional Teams