Senior QA Engineer - Generative AI Platform

Jobtailor; Milpitas (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Jobtailor is seeking a Lead QA Architect to own quality strategy for large-scale Generative AI products. You will design validation approaches for AI services, distributed systems, and customer experiences, while shaping scalable testing across pipelines, APIs, UIs, and multi-tenant SaaS environments.

You will mentor engineers, establish release-readiness gates, and drive data-driven decision making to improve AI platform reliability and resilience across cross-functional teams.

Qualifications

• Design and implement test strategies and automation for distributed software systems and cloud platforms.
• Validate AI services, frontend and backend systems with REST/GraphQL APIs and CI/CD pipelines.
• Evaluate model quality and degradation in Generative AI workloads.
• Define release-quality criteria and data-driven Go/No-Go decisions.
• Mentor QA engineers and drive quality-first engineering practices across teams.

Responsibilities

• Lead the quality strategy for large-scale Generative AI products and platforms.
• Define validation approaches forAI services, distributed systems, and end-to-end customer experiences.
• Design scalable testing and automation across AI pipelines, APIs, UIs, and multi-tenant SaaS architectures.
• Establish release-readiness practices using quality gates and data-driven criteria.
• Mentor QA engineers and advance quality-first practices across teams.

Skills

Quality Strategy Leadership

Test Strategy Design

Python Development

Automated Testing Frameworks

Generative AI Testing

Education

Bachelor’s Degree in Engineering or related field

Master’s Degree in Computer Science or Engineering

PhD with 2 years experience

Tools

Pytest

Playwright

Selenium

Cursor

Claude

Codex CLI

Kubernetes

ArgoCD

Job description

Jobtailor is seeking a Lead QA Architect to own quality strategy for large-scale Generative AI products. You will design validation approaches for AI services, distributed systems, and customer experiences, while shaping scalable testing across pipelines, APIs, UIs, and multi-tenant SaaS environments.

You will mentor engineers, establish release-readiness gates, and drive data-driven decision making to improve AI platform reliability and resilience across cross-functional teams.