[Hiring] Director, Quality Intelligence and Continuous Improvement @Nasuni

Role Description

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.

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.
• The capability scales to new platforms without unnecessary process.

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.

Company Description

Nasuni is the unstructured data foundation for enterprise teams and the AI that supports them. We manage, protect, and activate the world's unstructured data so organizations can work smarter, spend wisely, and create safely without limits. As a Vista-backed SaaS data infrastructure company, Nasuni is transforming how enterprises manage file data with a next-generation, AI-ready platform, turning massive file stores into secure, actionable data for intelligent automation, analytics, and global collaboration.

Why Work Here

Build on an established quality foundation at a pivotal moment as Nasuni improves the products customers depend on today and introduces new platforms and services. Work with talented Engineering and customer-facing teams, a dedicated Principal-level Data Scientist, and a CTO-sponsored cross-functional leadership team to shape a best-in-class capability with visible, lasting customer impact. Nasuni combines the opportunity to make a difference at a growing software company with Vista Equity Partners' broader operating expertise and innovation ecosystem.

Location

This role may be based in the Boston area or remotely within the United States. Boston-area candidates may collaborate onsite periodically; remote candidates should work effectively across U.S. and India time zones and travel for key planning or collaboration as needed.

Compensation Transparency

In accordance with U.S. pay transparency laws, Nasuni is committed to providing visibility into compensation for all U.S.-based roles. Actual compensation will be based on a variety of factors, including a candidate’s experience, skills, education, and work location.

Equal Opportunity Employer

Nasuni is an equal opportunity employer. The equal employment opportunity policy at Nasuni protects employees and job applicants from discrimination on the bases of race, religion, color, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, family medical history or genetic information, political affiliation, military service, or other non-merit based factors.