About The Position

Nasuni is building a dedicated quality intelligence and continuous improvement capability to assess product performance after release and turn evidence into measurable customer improvements. This senior, hands-on role is part of the CTO organization and focuses on defining and interpreting product and field health measures, including Edge Appliance availability, release reliability, engineering health, and support signals. The role connects existing telemetry, engineering, service, and support data; it does not require building a new data platform. The Director partners with a dedicated Principal Data Scientist and coordinates a cross-functional improvement forum whose contributors report to other teams. The role owns quality measures, executive-ready analysis, the action cadence, and validation of results, while functional leaders own implementation within their teams. It is expert-led work rather than a large QA or test-management role. The position may be based in the Boston area or remotely within the United States. Boston-area employees may collaborate onsite periodically. Remote employees should work effectively across U.S. and India time zones and travel for key planning or collaboration as needed. Compensation depends on factors including experience, skills, education, and work location; the posting refers candidates to compensation ranges by job grade but does not provide figures.

Requirements

  • Significant ownership of post-release quality, field reliability, technical operations, or continuous improvement in enterprise technology; typically 10+ years in relevant work.
  • Strong production knowledge of enterprise storage infrastructure, NAS/NFS, or distributed file systems, including hardware, protocol, and software interactions.
  • Track record of defining quality measures and delivering verified improvements across teams without reporting authority.
  • Sound data judgment with practical SQL, JQL, or comparable query experience, or the ability to regain hands-on fluency quickly.
  • Executive-ready communication skills and independence working with senior directors and VP/CTO stakeholders.
  • Evidence of personally building AI agents or repeatable AI workflows with validation, security safeguards, and useful results.
  • Demonstrated expertise and outcomes matter more than exact years of experience or specific tool names.

Nice To Haves

  • Experience with Snowflake, observability tooling, Linux diagnostics, cohort analysis, or service-level measures.
  • Experience in SaaS/cloud operations, OEM hardware/firmware, and globally distributed collaboration.
  • Applied Lean, Kaizen, DMAIC, 8D, or similar methods.
  • Established release-over-release field-quality measures that changed decisions.
  • Experience connecting support tickets to installed versions and closing recurring field defects.
  • Experience deploying repeatable, governed AI agents that saved time or improved quality.

Responsibilities

  • Create comparable measures for appliance availability, incidents, release quality, recovery, support burden, and team-level engineering delivery health.
  • Connect existing telemetry, support cases, installed code versions, engineering defects, and configuration data to explain field trends and release-to-release changes.
  • Investigate hardware, firmware, NFS/file-service protocols, Edge Appliance behavior, and cloud-service dependencies to identify systemic customer risks.
  • Help Support and Engineering map ticket volumes and incident categories to field defects and priorities, improving intake signals where useful.
  • Drive corrective and preventive action across post-sale teams by securing accountable owners, escalating blockers, and verifying improvements.
  • Prepare concise, decision-ready executive analysis that distinguishes evidence, uncertainty, potential customer exposure, and recommended actions.
  • Create lightweight operating practices and secure, validated AI agents or automation for investigation, classification, and follow-through.
  • Coordinate a cross-functional improvement forum and validate results while functional leaders implement changes within their teams.
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