Manager, Software QA Engineering & Reliability

Tenable•Columbia, MD

14h•Remote

About The Position

Tenable® is the Exposure Management company. 44,000 organizations around the globe rely on Tenable to understand and reduce cyber risk. Our global employees support 65 percent of the Fortune 500, 45 percent of the Global 2000, and large government agencies. Come be part of our journey! What makes Tenable such a great place to work? Ask a member of our team and they’ll answer, “Our people!” We work together to build and innovate best-in-class cybersecurity solutions for our customers; all while creating a culture of belonging, respect, and excellence where we can be our best selves. When you’re part of our #OneTenable team, you can expect to partner with some of the most talented and passionate people in the industry, and have the support and resources you need to do work that truly matters. We deliver results that exceed expectations and we win together! Your Role: We are seeking a highly experienced Manager of Quality Engineering who will lead the Quality function for an Exposure Management product with a strong focus on automation-first strategy, observability-driven quality insights, and data-backed decision making. This role is responsible for scaling test automation, strengthening release reliability, improving customer experience, and establishing a culture of engineering excellence across teams.

Requirements

7 –10+ years of experience in Quality Engineering, including 2–5 years leading teams.
Deep expertise in test automation frameworks, CI/CD pipelines, and cloud-based SaaS delivery.
Strong understanding of observability tools (Datadog, Grafana).
Hands-on experience with performance testing tools (JMeter, K6, etc).
Strong command over quality metrics, reporting, and KPI-driven decision making.
Excellent communication and stakeholder management skills.

Responsibilities

Define and execute the long-term Quality Engineering vision, aligned with product and engineering goals.
Establish an automation-first culture, ensuring test automation is embedded into CI/CD and development workflows.
Drive strategic initiatives in performance testing, security validation, observability, and production readiness.
Own the automation roadmap across UI, API, performance, integration, and end-to-end testing.
Increase automation coverage and ensure automation is a gatekeeper for every release.
Strengthen CI/CD pipelines by integrating AI-driven test creation, self-healing automation, and continuous validation.
Identify and introduce the right automation tools (Playwright, Postman, JMeter, etc.).
Implement and enhance observability practices using logs, metrics, traces, and synthetic monitoring.
Partner with DevOps/SRE to improve error budgets, reliability scorecards, SLO/SLA tracking, and early incident detection.
Drive real-time production quality visibility through dashboards (Datadog, New Relic, Grafana, Elastic).
Lead RCA processes and implement systemic fixes to reduce repeat issues/incidents.
Build a monthly Quality Insights report for leadership with actionable recommendations.
Use metrics to optimize team performance, raise quality standards, and guide investment decisions.
Strengthen release governance with quality gates, smoke automation, performance checks, and risk-based testing.
Ensure predictable, stable, and low-defect releases across environments.
Drive continuous improvements in regression cycles, test planning, automation strategy, and environment readiness.
Collaborate with Engineering, Product, UX, DevOps, and Support to embed quality early in the lifecycle.
Influence technical designs by advocating for testability, reliability, and observability.
Serve as the Quality representative in roadmap discussions, quarterly planning, and architecture reviews.
Lead, mentor, and grow a team of QA engineers, SDETs, automation architects, and analysts.
Build a culture of accountability, innovation, and continuous learning.
Enable the team with training in automation, performance, observability tools, and AI-driven testing.
Define, track, and present data-driven quality metrics such as: Automation coverage Escaped defect rate Release reliability score Regression stability User experience metrics Performance baselines & SLAs Incident trends