Director, Quality Intelligence and Continuous Improvement

Director, Product Quality & Continuous Improvement

CTO Organization | United States — Remote | Greater Boston/Marlborough Preferred

The Opportunity

Is the software we just released better than the release before it?

Nasuni is investing in a dedicated quality intelligence and continuous improvement capability to answer that question with evidence.

You will define how our products perform after release — from Edge Appliance availability and release reliability to team-level engineering health and support signals — then turn the findings into measurable improvements for customers.

The work connects existing telemetry, engineering, service, and support data; it does not require building a new data platform.

Level & Scope

This senior, hands-on position sits in the CTO organization. You will partner with a dedicated Principal Data Scientist and coordinate a cross-functional improvement forum whose contributors report elsewhere.

You own the quality measures, executive-ready analysis, action cadence, and validation of results; functional leaders own their teams' implementation.

This is expert-led work, not a large QA/test management role.

What You Will Lead

• Create comparable measures for appliance availability, incidents, release quality, recovery, support burden, and team-level engineering delivery health.
• Join 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; improve intake signals where useful.
• Drive corrective and preventive action across post-sale teams, securing accountable owners, escalating blockers, and verifying improvement rather than stopping at recommendations.
• Prepare concise, decision-ready executive analysis that separates 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.

What Success Looks Like

Leaders share a trusted view of product and field health; releases can be compared fairly; emerging issues are translated into actionable engineering work; cross-functional corrective actions close with verified impact; and the capability scales to new platforms without unnecessary process.

Must-Have Qualifications

• Significant post-release quality, field reliability, technical operations, or continuous improvement ownership 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 and the independence to work with senior directors and VP/CTO stakeholders.
• Evidence of personally building AI agents or repeatable AI workflows with validation, security safeguards, and useful results.

Preferred Qualifications

• Snowflake, observability tooling, Linux diagnostics, cohort analysis, or service-level measures.
• SaaS/cloud operations, OEM hardware/firmware, and globally distributed collaboration.
• Applied Lean, Kaizen, DMAIC, 8D, or similar methods.

Ideal Differentiators

• Established release-over-release field-quality measures that changed decisions.
• Connected support tickets to installed versions and closed recurring field defects.
• Deployed repeatable, governed AI agents that saved time or improved quality.

Experience Guidelines

Demonstrated expertise and outcomes matter more than exact years or specific tool names.

About Nasuni