Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security.
Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope.
About the role
Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience.
The Data QE team is responsible for the quality of data, data services, and data components across our cloud and hybrid cloud environments. We develop tools, create fully automated regression suites and conduct performance tests for distributed data components at cloud scale. If you thrive on solving difficult problems, complex test scenarios, and developing high-performance QE tooling and automation, we would love to discuss our career opportunities with you.
We are currently seeking a highly skilled Staff / Sr. Staff SDET to lead initiatives at the intersection of AI/ML, cloud security, data engineering, and network security. This role involves testing the product, data efficacy, building CI/CD pipelines, and automating tools and tests to deliver high quality AI-driven solutions to detect and mitigate cybersecurity threats in cloud environments. You will collaborate with cross-functional teams to deliver secure, efficient, innovative solutions addressing complex security challenges.
What’s in it for you
- You will be part of a growing team of renowned industry experts in the exciting space of AI/ML, Data Engineering and cloud / network security
- Your contributions will have a major impact on our global customer-base and across the industry through our market-leading products
- You will solve complex, interesting problems, and improve the depth and breadth of your technical and business skills.
What you will be doing
- Leading the test documentation, automation and deployment tooling of the microservice based architecture.
- Developing, executing, and maintaining manual and automated test cases for AI and infrastructure components.
- Designing and implementing test plans for backward compatibility, REST APIs and integration testing.
- Writing and maintaining test documentation to ensure transparency and repeatability of test processes.
- Automating testing using Python, Java or equivalent programming language to improve efficiency and coverage.
- Troubleshooting, debugging, and optimizing test environments in Kubernetes-based ecosystems.
- Collaborating with cross-functional teams, including data scientists, AI engineers, and DevOps, to ensure software quality.
- Staying up-to-date with the latest advancements in AI testing methodologies and tooling.
Required skills and experience
- 8+ years of experience
- Strong knowledge of automation and building automation frameworks
- Excellent knowledge of and coding skills with Python, Java, etc
- Good knowledge of microservice architecture, distributed systems and familiarity with k8s and docker
- Strong knowledge of building CI/CD pipelines with Jenkins or Github Actions
- Experience with cloud platforms like AWS, Azure or GCP
- Experience testing data pipelines for large scale data processing and testing data efficacy or data correctness.
- Familiarity with RAG systems, vector databases such as Pincone, PGVector, and LLMs to validate data pipelines and inference results.
- Familiarity with AI models or conceptual knowledge of AI models and prompt engineering.
- Familiarity with relational and non-relational databases, like ClickHouse and BigQuery.
- A proven ability to lead cross-functional teams and mentor more junior engineers.
- Excellent written and verbal communication skills and the ability to present complex technical concepts to stakeholders.
Education
- BSCS or equivalent required, MSCS or equivalent strongly preferred
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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.
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