Senior Quality Engineer – Generative AI & Enterprise Web Platforms

Senior Quality Engineer – Generative AI & Enterprise Web Platforms

  

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Job Description:

   

Job Family Definition:

Designs, develops, troubleshoots and debugs software programs for software enhancements and new products. Develops software including operating systems, compilers, routers, networks, utilities, databases and Internet-related tools. Determines hardware compatibility and/or influences hardware design.

Management Level Definition:

Contributions impact technical components of HPE products, solutions, or services regularly and sustainable. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross-functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others.

Responsibilities:

• Quality strategy and governance: Define risk-based test strategies, quality gates, release criteria, traceability, and measurable objectives across AI, UI, API, cloud, and network layers.

• Generative AI and agent validation: Evaluate model quality, groundedness, safety, privacy, robustness, tool use, permissions, failure recovery, latency, and cost.

• Application and integration testing: Validate React interfaces, web standards, accessibility, security, APIs, asynchronous workflows, and enterprise integrations.

• Cloud, network, and resilience testing: Test AWS deployments, distributed systems, traffic behaviour, scaling, failover, disaster recovery, and adverse network conditions.

• Performance and automation: Build reusable Python and pytest frameworks and execute performance, scale, reliability, and end-to-end testing with CI/CD integration.

• Production quality and continuous improvement: Use telemetry, incidents, and user feedback to detect regressions, strengthen coverage, and improve preventive controls.

• Collaboration and quality leadership: Partner across disciplines, use AI-assisted testing responsibly, mentor engineers, and promote shared ownership of quality.

Education and Experience Required:

• Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline

• 10 years’ experience with 3 years in a lead role

Knowledge and Skills:

• Quality strategy and governance: Define risk-based test strategies, quality gates, release criteria, traceability, and measurable objectives across AI, UI, API, cloud, and network layers.

• Generative AI and agent validation: Evaluate model quality, groundedness, safety, privacy, robustness, tool use, permissions, failure recovery, latency, and cost.

• Application and integration testing: Validate React interfaces, web standards, accessibility, security, APIs, asynchronous workflows, and enterprise integrations.

• Cloud, network, and resilience testing: Test AWS deployments, distributed systems, traffic behaviour, scaling, failover, disaster recovery, and adverse network conditions.

• Performance and automation: Build reusable Python and pytest frameworks and execute performance, scale, reliability, and end-to-end testing with CI/CD integration.

• Production quality and continuous improvement: Use telemetry, incidents, and user feedback to detect regressions, strengthen coverage, and improve preventive controls.

• Collaboration and quality leadership: Partner across disciplines, use AI-assisted testing responsibly, mentor engineers, and promote shared ownership of quality

• AI quality and observability: Experience with agent evaluation, prompt regression, model comparison, tracing, and production monitoring.

• Performance and resilience: Proficiency in API and browser performance testing, cloud-scale resilience, and chaos testing.

• Security and complex platforms: Knowledge of OWASP risks, threat modelling, adversarial validation, and testing multi-tenant or distributed enterprise architectures.

• AWS and monitoring: Familiarity with AI services, container platforms, and observability tools such as Datadog.

• Credentials and leadership: Relevant networking certifications and demonstrated leadership across automation, cloud quality, performance, security, or responsible AI.

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

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Job:

Engineering

Job Level:

TCP_04

    

    

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

   

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

   

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