Gong is looking for an experienced Director of Quality Engineering to join our R&D team and define how quality is managed, measured, and improved across Gong.

In this role, you will lead our Quality Engineering, SRE, and NOC teams. You will help Gong move from reactive quality and reliability operations toward an engineering-owned model in which teams ship with confidence, operate their services responsibly, and continuously learn from production.

A significant part of this mandate is to make Gong an AI-driven quality and reliability organization: using AI to prevent defects, understand change risk, detect customer impact, accelerate response, and continuously improve the systems and practices that keep Gong dependable.

As Senior Director of Quality & Reliability Engineering at Gong, you will

• Define and lead Gong’s quality and reliability strategy across R&D, including ownership expectations, standards, and metrics.
• Lead and coach the Quality Engineering, SRE, and NOC organizations, creating clear missions, healthy interfaces, and strong career growth.
• Establish a pragmatic quality-and-reliability operating model spanning design, development, production operations, incident response, and learning.
• Guide Gong’s QE methodology and tooling, including automation strategy, test architecture, test data, test environments, performance testing, and other non-functional quality practices.
• Set the direction for reliability engineering, including observability, alert quality, capacity and performance, incident management, and reduction of operational toil.
• Ensure that service teams own the reliability of their modules while SRE provides the standards, tooling, enablement, and cross-service visibility.
• Ensure the NOC provides effective triage, runbook execution, and operational coverage for the platform.
• Build a strong incident-management and post-incident learning culture: prioritize customer impact, coordinate response, identify systemic causes, and drive corrective actions to completion.
• Lead AI-driven quality and reliability across the lifecycle: from test design, regression, and flaky-test analysis to alert triage, incident response, postmortem automation, and decision support for capacity, rollout, mitigation, and rollback.
• Measure the impact of AI adoption through outcomes such as escaped-defect reduction, test-signal quality, alert-noise reduction, and time to detect and mitigate.

You should apply if you have

• Significant experience leading Quality Engineering, SRE, production engineering, or a comparable combination of quality and reliability functions in a complex SaaS or cloud-product environment.
• Experience leading multiple technical teams and managers, with a track record of building effective organizations, clarifying ownership, and developing leaders.
• Strong technical judgment across test architecture, automation, observability, service reliability, incident management, and production operations.
• Experience defining and operating observability standards, SLIs/SLOs, alerting, incident-response practices, postmortems, and on-call models.
• A demonstrated ability to help engineering teams improve quality and reliability through methodology, platforms, coaching, and practical standards rather than heavy process.
• Experience with AI-assisted testing, incident response, operational knowledge, or developer productivity workflows.
• Experience defining metrics and operating reviews that change behavior instead of creating reporting overhead.
• Excellent communication and stakeholder-management skills, including the ability to communicate risk clearly to both technical and executive audiences.
• Prior experience as a software engineer, automation architect, or technical operations leader.

This is not a traditional QA or operations role

This is a leadership role focused on building the system that makes quality and reliability a shared engineering responsibility. The goal is not to create a central gatekeeper or a team that absorbs every operational problem. The goal is to build the strategy, capabilities, standards, teams, and operating rhythm that enable Gong to deliver dependable customer outcomes at scale.

What makes working at Gong unique?

Here at Gong, we trust and empower our employees with ownership to solve complex problems, make the right decisions, and build products that create radical impact.

We call this “Own. Solve. Impact.”

About us

Gong empowers everyone in revenue teams to improve productivity, increase predictability, and drive revenue growth by deeply understanding customers and business trends. The Gong Revenue AI Platform captures and contextualizes customer interactions, surfaces insights and predictions, and powers actions and workflows that are essential for business success.

Here at Gong, we encourage employees to express their personality and identity, and we ensure fairness and equal opportunities

We follow a hybrid working model that combines working from home, on the go, and at the office.

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