Lead Software QA Engineer, AI Automation

WHO WE ARE  Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com . Why This Role Exists Most teams slow down to achieve quality. We believe the opposite: quality is what enables speed. We are building an AI-first engineering organization where developers ship fast, confidently, and continuously. That only works if someone owns the system of how quality, data, and delivery come together . That someone is you. This is not QA. This is not project management. This is a high ownership role where you shape how an AI-First team builds, validates, and ships production software. What You Will Own Make Quality a Built-In System, Not a Gate Turn quality into developer behavior , not a downstream function Teach engineers to anticipate failure modes, edge cases, and data issues before writing code Build automated test systems that act as guardrails , not overhead Define what “production-ready” actually means and enforce it through systems, not process Eliminate “hope-driven releases” Define What’s Buildable Before It Gets Built Partner with Sales and Product to pressure test ideas early Answer: Is this possible? With what data? At what cost? With what trade-offs? Translate ambiguity into clear execution plans engineers can run with Kill bad ideas early. Shape good ones into something buildable Own the Data Reality Map and understand how data actually flows , not how people think it flows Identify what data exists, what is missing, and what is unreliable Navigate internal systems and third-party integrations with confidence Ensure every feature is grounded in real, usable data, not assumptions Bring Domain Depth (MarTech / AdTech + Healthcare) Apply real-world understanding of identity, activation, measurement, and data constraints Operate within healthcare realities , including compliance and sensitivity of data Ensure what we build is not just technically correct, but market-relevant and viable Drive Delivery Like an Owner Run delivery for a team of AI-first engineers Break down work into clear, executable steps with no ambiguity Drive predictable delivery without slowing the team down Surface risks early and adjust before they become problems Align Product, Engineering, and GTM without friction Redefine QA for AI-First Development Build testing strategies for AI-generated and non-deterministic systems Validate outputs, not just code Create evaluation frameworks for AI reliability, accuracy, and behavior Ensure AI accelerates development without degrading quality What Makes You a Strong Fit You have likely outgrown traditional QA or delivery roles You think in systems, not tickets You can go from data model → product requirement → test strategy → delivery plan without handoffs You are comfortable pushing back on Product and Sales when things do not make sense You know how to make engineers better without becoming a bottleneck You care deeply about what happens in production , not just what gets shipped Your Background Likely Includes Deep experience in quality engineering, SDET, or technical delivery leadership Strong hands-on experience with test automation and CI/CD systems Ability to query and reason across complex data systems (SQL required) Experience with AI-assisted development or ML/LLM-based systems Strong familiarity with MarTech / AdTech ecosystems , healthcare is a major plus What Success Looks Like Engineers ship to production with confidence, not hesitation Bugs are caught before customers ever see them Automated tests are trusted, fast, and low maintenance Discovery is grounded in data reality, not assumptions Delivery is predictable without heavy process The team moves fast because quality is built in, not added later Why You Should Join You will define how an AI-first engineering organization actually operates You will have real ownership across quality, data, and delivery You will work on high-impact MarTech / AdTech problems in healthcare You will operate in a team that values speed, clarity, and production outcomes Bottom Line If you want