Principal Test Automation Engineer
About The Position
We are looking for a Principal Test Automation Engineer who combines deep storage domain expertise with the ability to build AI-native workflows that multiply engineering productivity, find bugs faster, and reduce escapes. You will set standards for AI-assisted validation workflows and scale best practices across the team. This role requires solid knowledge of SAS, SCSI, NVMe, NVMe-oF, and TCP, along with hands-on experience using AI to accelerate test creation, exploratory testing, triage, root cause analysis, and workflow automation. You will work across the full validation lifecycle — from requirements and user stories, to test planning and automation, to post-run triage, bug filing, documentation, and PR workflows — using tools like Jira and Jenkins, and MCP-enabled AI assistants. You won't just use existing tools; you'll build new ones where gaps exist. You'll join a team that is actively investing in AI-native engineering practices and with MCP integrations already connecting our AI workflows to tools like Jira and Jenkins, and a roadmap to expand further across our automation platform and REST APIs. You'll have the opportunity to shape how AI transforms our validation workflows, not just execute someone else's playbook.
Requirements
- B.S. or M.S. in Computer Science, Electrical Engineering, or related field
- Experience converting requirements and user stories into test plans, test cases, and automated validation using AI-assisted workflows.
- Experience applying AI tools in engineering workflows, including promp engineering, RAG, and tool/agent integrations (e.g., MCP); production experience is a plus, but strong demonstrated initiative counts.
- Strong experience in test automation and quality assurance, with significant focus on storage systems.
- Hands-on experience with Python and pytest
- Strong understanding of storage systems and validation methodologies
- Knowledge of SAS, SCSI, NVMe, NVMe-oF
- Understanding of TCP
- Strong Linux troubleshooting and system-level debugging skills
- Good understanding of hardware-software interaction
- Experience identifying coverage gaps, weak scenarios, and missing negative tests, with understanding of regression optimization and data-driven quality improvement
- Strong communication, collaboration, and problem-solving skills
- Self-driven and able to work effectively in a fast-paced environment
Nice To Haves
- Experience with AI-assisted IDEs (Windsurf, Cursor, Copilot) and custom workflow/rule authoring
- Active engagement with the AI landscape — you follow model releases, experiment with new tools, and bring relevant advances into your work.
- Experience testing REST APIs
- Experience with Fabric Switches
- Familiarity with RDMA/RoCE (used with NVMe-oF)
- Experience with HDD/SSD debugging
- Comfortable working in a lab/data center environment
- Experience building reusable automation frameworks, validation workflows, or engineering playbooks
- Familiarity with PR workflows, release validation, and engineering documentation
- Experience building internal tools and dashboards using Streamlit, Gradio FastAPI, or similar
Responsibilities
- Translate requirements, design docs, and user stories into test plans, test cases, and pytest automation using AI-assisted and MCP-enabled workflows.
- Drive AI-assisted exploratory testing by identifying edge cases, negative scenarios, recurring failure patterns, and coverage gaps.
- Build and operationalize AI-driven triage, root cause analysis, and failure trend analysis — correlate logs, traces, firmware output, and hardware events across subsystems; build tools and dashboards that surface patterns, cut MTTR, and deliver data-backed release-readiness signals.
- Build reusable AI-driven workflows, templates, and playbooks across tools like Jira and Jenkins — including RAG-based knowledge systems grounded in platform specs, historical failures, and engineering documentation for test creation, triage, bug filing, documentation, execution summaries, and PR preparation.
- Mentor team members on AI-assisted engineering practices, prompt engineering, and MCP workflow adoption.
- Develop automated tests using pytest for firmware and storage subsystem validation across JBOD, JBOF, NAS, and SAN platforms.
- Optimize regression efficiency through risk-based test selection, rerun strategy improvements, prioritization, and flaky test detection and reduction.
Benefits
- paid vacation time
- paid sick leave
- medical/dental/vision insurance
- life, accident and disability insurance
- tax-advantaged flexible spending and health savings accounts
- employee assistance program
- other voluntary benefit programs such as supplemental life and AD&D, legal plan, pet insurance, critical illness, accident and hospital indemnity
- tuition reimbursement
- transit
- the Applause Program
- employee stock purchase plan
- the WD Savings 401(k) Plan
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What This Job Offers
Job Type
Full-time
Career Level
Principal
