Staff QA Automation Engineer

Zeta Global; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

AI-driven work environment

Innovative company culture

Job summary

Zeta Global in Bengaluru is seeking a Quality Engineering expert to redefine QA for AI systems. You'll establish quality as a priority and oversee delivery for our AI-first engineering teams.

The ideal candidate should have a background in Quality Engineering and be adept at handling complex data systems. Strong SQL skills and experience with test automation are essential. Enjoy a fast-paced environment where you define our software delivery processes.

Qualifications

• Strong experience in quality engineering and data systems.
• Ability to develop automated testing frameworks.
• Confident in navigating complex data ecosystems.

Responsibilities

• Own delivery for AI-first engineering teams.
• Turn quality into developer behavior.
• Develop testing strategies for AI-generated systems.

Skills

Strong systems thinking across quality, data, and delivery

Ability to move from data models to delivery plan

Experience improving engineering quality

Focus on production outcomes

Education

Background in Quality Engineering, SDET, or technical delivery leadership

Tools

Test automation

CI/CD pipelines

Strong SQL skills

Job description

• Most teams trade speed for quality. We believe quality is what enables speed.
• We are building an AI-first engineering organization where teams ship fast, confidently, and continuously. That only works when quality, data, and delivery are designed as a system—not separate functions.
• This is not a traditional QA role. It is not project management. This is a high‑ownership position where you define how an AI‑first team builds, validates, and ships production software.

Key Responsibilities

• Build Quality as a System
  • Turn quality into developer behavior, not a downstream gate
  • Design automated testing systems that act as guardrails
  • Define and enforce what “production-ready” means through systems
  • Enable teams to anticipate edge cases, failures, and data issues early
  • Eliminate “hope-driven” releases
• Define What’s Buildable
  • Partner with Product and Sales to validate ideas early
  • Assess feasibility, data requirements, trade‑offs, and cost
  • Translate ambiguity into clear, executable plans
  • Shape viable ideas and stop unworkable ones early
• Own the Data Reality
  • Map how data actually flows across systems and integrations
  • Identify gaps, inconsistencies, and reliability issues
  • Ensure features are grounded in real, usable data
  • Navigate internal and third‑party data ecosystems confidently
• Bring Domain Expertise
  • Apply knowledge of MarTech / AdTech (identity, activation, measurement)
  • Operate within healthcare data constraints and compliance requirements
  • Ensure solutions are technically sound and market‑relevant
• Drive Delivery End-to-End
  • Own delivery for AI‑first engineering teams
  • Break down work into clear, actionable steps
  • Maintain predictable delivery without slowing velocity
  • Proactively identify risks and adjust early
  • Align Product, Engineering, and GTM teams.
• Redefine QA for AI Systems
  • Develop testing strategies for AI‑generated, non‑deterministic systems
  • Validate outputs and behavior, not just code
  • Build evaluation frameworks for AI reliability and accuracy
  • Ensure AI accelerates development without compromising quality

What You Need to Succeed

• Strong systems thinking across quality, data, and delivery
• Ability to move from data models → requirements → test strategy → delivery plan
• Experience improving engineering quality without becoming a bottleneck
• Confidence pushing back on unclear or unviable ideas
• Focus on production outcomes, not just releases

Core Experience

• Background in Quality Engineering, SDET, or technical delivery leadership
• Hands‑on experience with test automation and CI/CD pipelines
• Strong SQL skills and ability to work with complex data systems
• Experience with AI‑assisted development or ML/LLM‑based systems

Nice to Have

• Experience in MarTech / AdTech ecosystems
• Familiarity with healthcare data, compliance, and constraints
• Exposure to building or testing AI‑first or non‑deterministic systems at scale

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin, or any other basis protected by applicable federal, state or local law; nor does Zeta discriminate on the basis of sexual orientation or gender identity or expression.

As set forth in Zeta Global’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.