Principal AI Go-to-Market Operations Engineer

Remote from: Mexico
Salary, yearly, USD: 75,000
Department: Business Development
Employment type: Full Time,
Job posted: 3 Jul 2026
Apply before: 3 Aug 2026
Experience level: Senior
Views / Applies: 27 / 1

About company

About QAD, Inc.

QAD is a leading provider of next-generation manufacturing and supply chain solutions in the cloud.

Computer Software
1979

Actively Hiring

AI Summary

This is a highly technical and strategic role at QAD, a SaaS company. The Principal AI Go-to-Market Operations Engineer will architect an AI-first GTM ecosystem, bridging Sales, RevOps, Marketing, and Customer Success. Responsibilities include building custom AI integrations, optimizing the revenue tech stack, and driving cross-functional efficiency. The ideal candidate has 5+ years in Revenue Operations or GTM Engineering, coding skills (Python, JavaScript), and deep knowledge of B2B GTM tools like Salesforce and Outreach. This role is central to enhancing pipeline generation, deal velocity, and reducing administrative friction.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight This role demands a rare combination of software engineering, data science, and revenue strategy expertise, making it highly complex and challenging to fill.

Salary Analysis

AI Insight The provided salary starts at $75,000, which is below market for a principal-level role. Based on US market data for similar positions, the median is approximately $170,000, with a typical range of $120,000 to $220,000. The offered salary may need adjustment to attract top talent.

Core Skills Required

Python Salesforce Artificial Intelligence Revenue Operations CRM Integration Data Science B2B SaaS AI Agent Orchestration Predictive Modeling GTM Strategy

Cover Letter Sample

Dear Hiring Manager,

I am excited to apply for the Principal AI Go-to-Market Operations Engineer role at QAD. With over 6 years of experience in revenue operations and AI-driven GTM strategies, I have a proven track record of architecting and deploying custom AI integrations that optimize sales pipelines and reduce costs. At my previous company, I built an AI agent orchestrator that connected Salesforce, Outreach, and Gong, resulting in a 30% increase in deal velocity and a 20% reduction in vendor spend.

My technical expertise in Python, JavaScript, and AI agent orchestration, combined with deep knowledge of the B2B SaaS stack, makes me confident I can drive QAD's revenue engine to new heights. I am passionate about building systems that augment human effort rather than replace it, ensuring seamless adoption across GTM teams.

I look forward to the opportunity to discuss how I can contribute to QAD's mission. Thank you for your consideration.

Sincerely, [Your Name]

Sample Interview Questions

Describe a time you built a custom AI integration from scratch to solve a GTM problem. What tools and languages did you use, and what impact did it have?

At my last role, I used Python to build an AI-powered lead enrichment tool that pulled data from multiple sources via APIs and fed it into Salesforce. This reduced manual data entry by 40% and improved lead-to-account matching accuracy by 25%.

How do you approach consolidating a tech stack to reduce vendor spend? Can you provide an example?

I conduct a thorough audit of all tools, mapping them to business needs. In one case, I replaced three separate tools (lead scoring, email sequencing, and analytics) with a single AI-driven platform, saving $200k annually while improving lead conversion rates by 15%.

Explain how you would use predictive modeling to identify high-intent pipelines and provide 'Next Best Action' recommendations.

I would build a model using historical CRM data to score leads and opportunities based on engagement, firmographics, and intent signals. The model would trigger automated recommendations, like sending a personalized case study or scheduling a demo, directly to the sales rep's dashboard.

How do you manage multiple AI agents working on different segments simultaneously to prevent conflicts and maintain data quality?

I use a central orchestrator that assigns tasks to agents based on segment rules and deduplication logic. I also implement a common data hub (e.g., Salesforce) where all actions log, with conflict resolution algorithms to handle overlaps. Regular audits ensure data quality.

What is your philosophy on when AI should replace human effort versus augment it in a GTM context?

AI should replace repetitive, low-judgment tasks like data entry and scheduling, allowing humans to focus on high-value activities like relationship building and strategic decision-making. Augmentation is key for tasks like drafting emails, where AI provides a starting point but the human adds personalization and context.

Company Description

QAD is a world-class SaaS company, and we are growing. We are looking for talented individuals who want to join us on our mission to help solve relevant real-world problems in manufacturing and the supply chain.

Job Description

We are seeking a visionary and highly technical AI Go-To-Market (GTM) Engineer to sit at the core of our revenue engine. This is not a traditional operations role; it is a hybrid of software engineering, data science, and revenue strategy. You will be responsible for architecting an AI-first GTM ecosystem that bridges the gap between Sales, RevOps, Marketing, and Customer Success.

Your goal is to ensure that every individual in our GTM organization and every piece of our technology stack is augmented by Artificial Intelligence. You will build the bridges that allow us to generate more pipeline, accelerate deal velocity, and eliminate administrative friction, all while optimizing our tech spend.

Responsibilities:

1. AI Architecture & Custom Integration

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.

2. Revenue Ecosystem Optimization

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.

3. Cross-Functional Efficiency

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.

Qualifications

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. You don’t need to be a software engineer, but you need to ship working code, not just configure no-code tools.
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. If someone says “we need 20 opportunities per quarter at 20% win rate and $75K ASD,” you should immediately know where AI can compress that funnel.
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.

Additional Information

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.
Compensation packages based on experience and desired skill set

About QAD and QAD Redzone:

QAD Inc. is a leading provider of adaptive, cloud-based enterprise software and services for global manufacturing companies. Global manufacturers face ever-increasing disruption caused by technology-driven innovation and changing consumer preferences. In order to survive and thrive, manufacturers must be able to innovate and change business models at unprecedented rates of speed. QAD calls these companies Adaptive Manufacturing Enterprises.

QAD Redzone helps to enable QAD’s vision for the Adaptive Enterprise. Labor productivity improvements directly impact efficiency. Productive and empowered employees increase the effective capacity of your plant and accelerate time to productivity for new employees giving manufacturers the agility to increase production beyond what was previously possible without having to invest in production equipment or new plants, and reduce the amount and impact of employee attrition. Empowered employees with a growth mindset take extreme ownership of challenges that impact their production goals, creating resilience in the face of disruption.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

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