This role pays more than
71%
of similar roles. Most pay
$151,000–$214,000
— the shaded band above.
At the midpoint, this role pays about
$206k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About Cisco
Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity
Cisco currently has
197 open roles
on FindRole.
Listed pay typically runs
$167,700–$245,200
across 197 roles with salary data.
As a Senior Software QA Engineer on the AI Software & Platform team, you will lead the quality strategy for large-scale Generative AI products and platforms. You will be responsible for defining how to validate AI services, distributed systems, and end-to-end customer experiences while designing scalable testing and automation across AI pipelines, APIs, user interfaces, federated microservices, and multi-tenant SaaS architectures. Your daily work involves establishing release-readiness practices, analyzing model degradation, and performing root-cause analysis on system failures to improve reliability. You will utilize Python, Pytest, Playwright, Selenium, REST/GraphQL APIs, and CI/CD pipelines to ensure quality. The role focuses on the technical challenges of validating LLM-powered applications, AI agents, and complex multi-tenant cloud environments involving Kubernetes, ArgoCD, and various model versions to ensure high performance in a distributed software ecosystem.
Lead the quality strategy for large-scale Generative AI products and distributed systems.
Design scalable testing and automation across AI pipelines, APIs, and multi-tenant SaaS architectures.
Establish release-readiness practices using measurable quality gates and data-driven Go/No-Go criteria.
Perform root-cause analysis on model degradation, system failures, and test instability to improve reliability.
Develop automated testing frameworks and infrastructure for cloud platforms and distributed microservices.
Mentor QA engineers and promote quality-first engineering practices across multiple technical teams.
What we're looking for
Bachelor's degree in Engineering or related field with 6 years experience, Master's with 4 years, or PhD with 2 years.
Experience designing and implementing test strategies, automation frameworks, and infrastructure for distributed systems, cloud platforms, or SaaS products.
Python development experience and proficiency with automated testing frameworks such as Pytest, Playwright, Selenium, or equivalent.
Experience validating frontend/backend systems, including REST/GraphQL APIs, service integrations, CI/CD pipelines, and microservice architectures.
Experience defining release-quality criteria and diagnosing system failures using logs, metrics, and other engineering data.
Experience testing Generative AI, AI/ML platforms, or LLM-powered applications, including evaluation of model quality (preferred).
Experience designing AI-agent-assisted QA workflows using tools like Cursor, Claude, or Codex CLI (preferred).
Experience testing multi-tenant cloud platforms and managing complex environments with Kubernetes and ArgoCD (preferred).
Python
Go
Java
C++
Kubernetes
OCI
PyTorch
TensorFlow
Hugging Face Transformers
LLMs
Generative AI
CI/CD
Microservices
Distributed Systems
Data Pipelines
Service Mesh