Senior Software QA Engineer, AI Software​/Platform Team

• Lead the quality strategy for large-scale Generative AI products and platforms
• Define validation approaches for AI services, distributed systems, and end-to-end customer experiences
• Design scalable testing and automation across AI pipelines, APIs, user interfaces, federated microservices, and multi-tenant SaaS architectures
• Establish release-readiness practices using quality gates, test traceability, production-representative environments, and data-driven Go/No-Go criteria
• Analyze model degradation, system failures, and test instability
• Drive root-cause analysis to improve AI platform reliability and resilience
• Partner with Engineering, Product, UX, Dev Ops, Documentation, and Customer Engineering
• Mentor QA engineers and advance quality-first engineering practices across teams

• Bachelor’s Degree in Engineering or a related field and 6 years of relevant experience, or Master’s Degree in Computer Science or Engineering and 4 years of experience, or PhD and 2 years of practical experience
• Experience designing and implementing test strategies, automation frameworks, and test infrastructure for distributed software systems, cloud platforms, or SaaS products
• Python development experience
• Experience with automated testing frameworks such as Pytest, Playwright, Selenium, or equivalent
• Experience validating frontend and backend systems, including REST and/or GraphQL APIs, service integrations, CI/CD pipelines, and distributed microservice architectures
• Experience defining release-quality criteria and diagnosing system failures using test results, logs, metrics, and other engineering data
• Experience testing Generative AI, AI/ML platforms, AI agents, LLM-powered applications, or other AI-based products
• Experience evaluating model quality and degradation
• Experience designing AI-agent-assisted QA workflows using tools such as Cursor, Claude, Codex CLI, or equivalent
• Experience with agent-based or MCP-based test orchestration
• Experience testing multi-tenant cloud platforms and managing AI test environments involving datasets, model versions, feature flags, Kubernetes, and ArgoCD or similar deployment technologies
• Experience building scalable test frameworks and establishing practices across multiple engineering teams
• Knowledge of security, privacy, data governance, or compliance requirements relevant to enterprise SaaS and AI products

Demonstrates expertise in leading quality strategies for Generative AI products, including designing scalable testing and automation frameworks, validating AI services, and establishing release-readiness practices. Proficient in Python development and automated testing frameworks, with a strong focus on improving AI platform reliability and resilience.

• Quality Strategy Leadership
• Test Strategy Design
• Python Development
• Automated Testing Frameworks
• Generative AI Testing

• Test Strategy Design
• Automation Frameworks
• Python Development
• REST APIs
• GraphQL APIs
• CI/CD Pipelines
• Distributed Systems Testing
• Model Quality Evaluation
• Test Orchestration
• Multi-Tenant Cloud Platforms

• Mentoring
• Collaboration
• Root-Cause Analysis

• Generative AI
• AI/ML Platforms
• Data Governance
• Compliance Requirements
• Quality Gates

• Pytest
• Playwright
• Selenium
• Cursor
• Claude
• Codex CLI
• Kubernetes
• ArgoCD