Software Engineer II, RIS Test

HPE•Sunnyvale, CA

13d•$105,500 - $213,500•Onsite

About The Position

This Software Engineer II, RIS Test will play a critical role in designing, automating, and executing complex system‑level tests for networking products. This role requires strong expertise in Python automation, networking technologies, AI‑driven testing methodologies, and customer‑focused problem solving. The ideal candidate is highly analytical, collaborative, and adaptable, with a passion for improving product quality through intelligent automation and deep technical insight.

Requirements

Strong proficiency in Python and automation frameworks.
Hands‑on experience with networking protocols, CoS, Firewall, GRE, sFlow, jFlow.
Experience with Spirent, Ixia, or similar test equipment.
Familiarity with PyTest, Robot Framework, and automation best practices.
Excellent debugging, analytical, and communication skills.
Ability to work in fast‑paced, cross‑functional environments.
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.

Nice To Haves

Experience with AI‑driven testing tools and LLM‑based analysis is highly desirable.

Responsibilities

Automate test cases using advanced scripting techniques and languages such as Python.
Leverage internal infrastructure to ensure automated scripts run seamlessly across multiple test platforms.
Review automated scripts with stakeholders and integrate them into mainline regression suites.
Own the test suite by addressing issues reported in automated scripts and ensuring long‑term maintainability.
Participate in major customer escalations to understand, investigate, and narrow down platform, feature, or design‑related issues.
Replicate customer‑reported problems in lab environments to support development teams in identifying potential fixes.
Analyze field‑deployment issues, perform root‑cause analysis, and identify gaps in test coverage.
Investigate test gaps, reproduce issues in lab setups, and automate coverage to ensure continuous regression testing in future releases.
Work with Product Managers to identify deployment scenarios for new features.
Share deployment insights and best practices with other system test engineers.
Develop deep expertise in networking and software technologies relevant to the product.
Engage in technical forums and continuous learning to stay current with industry trends.
Strong automation background with expert‑level Python skills to design and develop automation scripts, tools, and frameworks.
Proven ability to build custom automation libraries, implement complex algorithms, and work with PyTest and Robot Framework.
Demonstrated expertise in Class of Service (CoS), Firewall/ACL technologies, and tunneling features such as static GRE tunnels.
Strong knowledge of network sampling technologies including sFlow and jFlow.
Hands‑on experience with networking test equipment such as Spirent and Ixia for testing and validation.
Ability to automate workflows related to test equipment is a strong plus.
Experience handling customer cases, understanding requirements, and delivering effective solutions.
Proven ability to conduct customer Proof of Concepts (POCs) and contribute to network solution design.
Strong analytical mindset with the ability to isolate, debug, and troubleshoot complex issues efficiently.
Strong analytical and debugging abilities with a proven track record of efficiently troubleshooting complex issues.
Excellent interpersonal and communication skills, enabling effective collaboration with customers, team members, and stakeholders.
Highly adaptable, self‑driven, quick to learn new technologies, and a strong team player who contributes positively to collective goals.
Leverage AI tools to analyze design documents, generate test scenarios, identify edge cases, and highlight risk areas.
Use AI assistants to create automation scripts, refactor existing code, and convert manual test cases into automated workflows.
Apply AI‑based debugging for intelligent log interpretation, flaky‑test detection, failure‑pattern prediction, and test‑coverage recommendations.
Utilize AI for packet‑capture analysis, network‑telemetry insights, and performance‑regression detection.
Hands‑on experience with AI‑generated test cases, intelligent coverage analysis, AI‑based regression testing, and LLM‑driven log analysis.