Netskope
About this role
Netskope builds cloud security infrastructure, and this is a specialist performance engineering role rather than general QA. The work is designing performance test strategies covering load, stress, volume and endurance, building reusable test scripts across HTTP, web services, APIs and file transfer protocols, and deploying containerised load generators such as JMeter, k6 or Locust directly onto Kubernetes to simulate scale with minimal overhead. The analysis half is the interesting part: deep dives into results to find bottlenecks in application code, database performance, network latency and infrastructure resource use, then working with developers and architects on tuning recommendations. Notably the posting asks for machine learning and AI concepts applied across the performance test cycle, and experience with AI capable monitoring tools such as Dynatrace, New Relic, Datadog or Grafana. 8+ years, Bengaluru.
Who this is for
Required by the posting: a minimum of 8 years of experience in performance testing and engineering roles with scalable cloud native multi tenant architectures. Proven expertise with at least one major performance testing tool, with JMeter, Locust, LoadRunner, Gatling, k6 and BlazeMeter named. Strong proficiency in at least one scripting or programming language for test development and customisation, with Java, Python, Golang and JavaScript named. Hands on experience with Docker and Kubernetes, including understanding how container resource limits affect application performance. Solid understanding of system architecture components including web servers, application servers, databases and load balancers. Experience with modern APM and monitoring tools incorporating AI/ML capabilities such as Dynatrace, New Relic, Prometheus, Grafana or Datadog. Working knowledge of SQL and NoSQL databases with the ability to analyse and optimise query performance. Strong analytical skills to interpret large datasets and AI generated outputs such as log traces and metrics to pinpoint root causes. Proficiency in machine learning and AI concepts including supervised learning and predictive modelling, and their application across the performance test cycle.
Preferred skills: experience with cloud platforms including AWS, Azure and GCP and testing applications deployed in cloud native environments, and familiarity with continuous integration and continuous delivery pipelines.
The real day to day: developing comprehensive performance test strategies and plans covering load, stress, volume and endurance testing; designing and maintaining robust, reusable test scripts for protocols including HTTP, web services, APIs and FTP/SFTP; collaborating with DevOps and infrastructure teams to configure performance test environments that accurately replicate production; designing and deploying containerised load generators onto the Kubernetes cluster to simulate massive scale with minimal overhead; executing tests and conducting deep dive analysis to identify bottlenecks in application code, database performance, network latency and infrastructure resource use; documenting clear reports with metrics and actionable recommendations for engineering and product stakeholders; working with developers and architects on performance tuning and code optimisation; and contributing to continuous improvement of the testing framework.
Location: Bengaluru, Karnataka.
Honest fit guidance: performance engineering at this depth is a genuine specialism, and eight years of functional test automation is not the same thing. The distinguishing requirements here are the Kubernetes native load generation and the expectation that you can read APM output and pinpoint root causes across code, database, network and infrastructure. The machine learning requirement is worth noting as a trend rather than a barrier: it is asking you to apply ML concepts to test analysis, not to build models. One relevant note from previous editions: Netskope has stated on other postings that it hires across all levels and levels candidates individually after assessment, so its stated year figures have historically been softer than they look.
Preferred skills: experience with cloud platforms including AWS, Azure and GCP and testing applications deployed in cloud native environments, and familiarity with continuous integration and continuous delivery pipelines.
The real day to day: developing comprehensive performance test strategies and plans covering load, stress, volume and endurance testing; designing and maintaining robust, reusable test scripts for protocols including HTTP, web services, APIs and FTP/SFTP; collaborating with DevOps and infrastructure teams to configure performance test environments that accurately replicate production; designing and deploying containerised load generators onto the Kubernetes cluster to simulate massive scale with minimal overhead; executing tests and conducting deep dive analysis to identify bottlenecks in application code, database performance, network latency and infrastructure resource use; documenting clear reports with metrics and actionable recommendations for engineering and product stakeholders; working with developers and architects on performance tuning and code optimisation; and contributing to continuous improvement of the testing framework.
Location: Bengaluru, Karnataka.
Honest fit guidance: performance engineering at this depth is a genuine specialism, and eight years of functional test automation is not the same thing. The distinguishing requirements here are the Kubernetes native load generation and the expectation that you can read APM output and pinpoint root causes across code, database, network and infrastructure. The machine learning requirement is worth noting as a trend rather than a barrier: it is asking you to apply ML concepts to test analysis, not to build models. One relevant note from previous editions: Netskope has stated on other postings that it hires across all levels and levels candidates individually after assessment, so its stated year figures have historically been softer than they look.
Apply on company site
Opens www.netskope.com, the employer's own application page. Applying is always free.