Staff / Sr. SDET , AI Gateway
Netskope · Taipei
Join the Future of Security at Netskope
Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud, data, and AI in real time, everywhere. Thousands of customers, including more than 30 of the Fortune 100, trust the Netskope One platform, its Zero Trust Engine, and the powerful NewEdge network to gain full visibility and control without performance trade-offs.
At Netskope, our technology is driven by our greatest strength: our people. We believe that belonging powers innovation, and success is both personal and organizational. We embrace differences in gender, ethnicity, beliefs, ability, and identity, creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work, grow their careers through continuous education and mentorship, and lead with transparency and curiosity. Join a team where you belong, where you are encouraged to be an entrepreneur, and where together, we continue to redefine the landscape of security.
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About the Role
Netskope AI Gateway helps global enterprises securely adopt and scale Generative AI. We are looking for a Senior or Staff Software Development Engineer in Test (SDET) to drive quality across AI Gateway features, services, and APIs in SaaS and on-premises/hybrid environments.
This is a hands-on engineering role combining software development, test automation, and quality engineering. You will own quality for assigned features or product areas, design effective test strategies, build reliable automation, and collaborate with Engineering and Product to deliver high-quality software.
We value engineers with strong testing fundamentals, practical coding skills, and the ability to investigate complex problems across system components. We are hiring at either the Senior or Staff level, depending on demonstrated technical depth, independence, and scope of ownership.
What You Will Be Doing
- Quality Ownership & Test Strategy: Own quality for assigned features or product areas. Translate requirements and architecture into risk-based test plans covering component, API, integration, and end-to-end scenarios.
- Hands-on Test Automation: Design, implement, and maintain automated tests, reusable utilities, fixtures, and frameworks using Python or Golang. Ensure code quality, reliability, and maintainability.
- API & Gateway Testing: Validate APIs, backend services, gateway behavior, authentication, policy enforcement, and cross-component workflows.
- CI/CD & Test Reliability: Integrate tests into CI/CD, improve execution efficiency, reduce flakiness, and troubleshoot pipeline and environment issues.
- Debugging & Defect Investigation: Analyze failures using logs, traces, and system behavior. Collaborate with developers on root-cause analysis and regression prevention.
- AI-Assisted Engineering: Use AI coding tools to accelerate test development and debugging while critically reviewing generated code and assertions.
- Collaboration & Technical Influence: Work with Engineering and Product to identify risks early, improve testability, support release readiness, and drive quality improvements.
What Success Looks Like
- Features and product areas ship with meaningful test coverage and understood risks.
- Automation is reliable, maintainable, and provides trustworthy results.
- Defects are identified and investigated efficiently, with regression coverage to prevent recurrence.
- CI/CD provides actionable feedback and supports timely releases.
- AI-assisted workflows improve productivity without compromising test quality.
- Quality improvements extend beyond individual test cases through effective engineering collaboration.
Required Skills and Experience
- Experience: 6+ years in software quality engineering, SDET, or test automation, with experience testing backend services, distributed systems, cloud applications, or networking/security products.
- QE Fundamentals: Strong understanding of test strategy, planning, risk-based testing, and test design across multiple testing layers.
- Programming & Automation: Strong hands-on Python (preferred) or Golang skills. Experience with pytest or similar frameworks, including fixtures, test data, mocking, and maintainable automation code.
- API & Integration Testing: Experience automating REST APIs, backend services, and integration workflows, including authentication, validation, and error handling.
- CI/CD: Experience developing and troubleshooting automated test pipelines using GitHub Actions, Jenkins, GitLab CI, or similar tools.
- Debugging: Ability to investigate failures across services and environments using logs, test results, and system behavior.
- Infrastructure & Networking: Practical experience with Docker, familiarity with Kubernetes, and working knowledge of HTTP/HTTPS, TLS, DNS, and proxy concepts.
- AI-Assisted Development: Familiarity with AI coding tools and the ability to understand, review, and validate generated code.
- Communication: Effective English communication and cross-functional collaboration skills.
Additional Expectations for Staff Level
Candidates considered for the Staff level should demonstrate greater technical depth, autonomy, and influence beyond the Senior requirements:
- Broader Quality Ownership: Independently own quality for significant product areas or services, including testing direction, risk assessment, coverage trade-offs, and release readiness decisions.
- Automation Architecture: Design and improve scalable test automation frameworks and infrastructure, addressing reliability, maintainability, execution efficiency, and test isolation while remaining hands-on with implementation.
- Advanced Problem Solving: Lead complex investigations across distributed services, infrastructure, Kubernetes, and networking boundaries, driving issues to root cause and implementing systemic improvements.
- Technical Leadership: Influence architecture, testability, and quality decisions across teams. Mentor engineers and drive improvements beyond assigned features without requiring formal management authority.
- AI-Assisted QE Practices: Apply AI-assisted engineering effectively to complex testing and debugging workflows, identify limitations in generated code, and help improve the team's engineering practices.
Nice to Have
- Experience with LLM provider APIs (OpenAI, Anthropic, Google Gemini, Amazon Bedrock) and streaming behavior.
- Cloud platform experience (AWS, Azure, GCP), including hybrid/on-premises deployments.
- Knowledge of cybersecurity, ZTNA, DLP, authentication, or gateway/proxy products.
- Experience with performance, load, resilience, or distributed systems testing.
- Familiarity with observability tools such as Prometheus, Grafana, ELK, or OpenTelemetry.
- Experience designing large-scale automation frameworks or improving QE practices across teams.
Education
Bachelor's degree in Computer Science or a related field, or equivalent practical experience. Master's degree is a plus.
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Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate.
The application window for this position is expected to close within 50 days. You may apply by filling out the below information, or visiting our Netskope Careers site.