Job Description
Introduction:
Are you searching for an opportunity to play a key role in driving the dramatic growth of a highly successful software company?
At Poppulo, we’re working on what’s next in communications and workplace technology. As a pioneer in this industry, we understand that meaningfully reaching every employee is hard. And so is managing office space in a hybrid world. And so is improving the customer and guest experience. We exist to make each of these things easier. We exist to bring harmony to our customers.
And we do that at enterprise scale. Our omnichannel employee communications, customer communications, and workplace experience platform is trusted by over 6,000 organizations today, reaching more than 35M employees and delivering content to 500,000+ digital signs.
We know there’s no such thing as a “perfect” candidate - we’re all a work in progress and are growing new skills and capabilities all the time. We encourage you to apply for a position with Poppulo even if you don’t meet 100% of the requirements. We believe in fostering an environment where there is a diversity of perspectives, in hopes that we can all thrive.
Job Summary
We are seeking an experienced Quality Engineering Manager to lead the quality function supporting Poppulo’s Digital Signage platform. This leader will be responsible for building and developing a high-performing Quality Engineering team in India that owns meaningful quality strategy, automation, evaluation, and delivery outcomes for the DS platform.
The Quality Engineering Manager will champion quality engineering practices throughout the software development lifecycle, ensuring that testing is integrated into every stage of delivery. This role combines people leadership with technical leadership, establishing scalable test automation frameworks, improving CI/CD quality gates, and driving continuous improvements that enable faster, more reliable software releases.
This role will help DS evolve from today’s quality and automation practices toward a more telemetry-driven, flow-oriented, and AI-enabled quality model. We do not expect every future capability to exist on day one; this leader will strengthen the current quality foundation while helping define, pilot, and scale the next generation of quality practices.
Working closely with Engineering, Product Management, UX, and DevOps, the Quality Engineering Manager will foster a culture of shared ownership for quality while mentoring Quality Engineers, Software Engineers, and automation-focused team members as the function evolves toward broader quality engineering and evaluation practices.
Key Responsibilities
Quality Transformation & AI Readiness
This leader will help DS move from traditional QA management toward a modern quality engineering model. They will improve current automation, CI/CD feedback, release readiness, and quality metrics while piloting responsible AI-assisted practices that can reduce manual overhead and improve confidence. The role requires a pragmatic leader who can operate in today’s environment while building toward a future where quality is supported by automation, telemetry, AI-assisted workflows, and strong human judgment.
Leadership & Team Management
- Build, lead, mentor, and grow a high-performing Quality Engineering team based in India.
- Establish clear goals, performance expectations, career development plans, and succession planning for the Quality Engineering organization.
- Foster a culture of collaboration, accountability, continuous learning, and engineering excellence.
- Recruit, onboard, and develop top quality engineering talent while promoting best practices across the organization.
- Partner with global Engineering leadership to align quality initiatives with business objectives.
- Establish collaboration practices that work across distributed teams, including clear written context, async-friendly documentation, structured handoffs, and protected overlap for high-value planning and review.
Quality Strategy & Automation
- Define and execute an automation-first, telemetry-informed Quality Engineering strategy that supports rapid, reliable software delivery.
- Drive adoption of modern automation frameworks for UI, API, integration, and end-to-end testing.
- Champion a whole-team quality mindset where testing is integrated into planning, design, development, and deployment.
- Establish quality metrics, dashboards, and delivery intelligence that combine CI/CD signals, defect trends, test health, release readiness, and executive-ready reporting.
- Continuously improve testing processes, automation coverage, and release confidence.
- Define a pragmatic roadmap for AI-assisted quality engineering, including opportunities for AI-supported test generation, synthetic data creation, defect triage, log analysis, MR review support, and delivery reporting.
- Help establish responsible use guidelines for AI-assisted quality work, including human review gates, traceability, data handling expectations, and measurable quality outcomes.
Technical Leadership
- Provide technical leadership for automation architecture, frameworks, and tooling.
- Ensure automated testing is fully integrated into CI/CD pipelines to provide rapid feedback and prevent regressions.
- Guide teams on test strategy, risk-based testing, exploratory testing, and non-functional testing.
- Promote best practices for API testing, UI automation, performance testing, security testing, and test data management.
- Support testing of cloud-native, distributed, and event-driven applications.
- Guide the team toward evaluation-style quality practices, including regression datasets, automated quality gates, risk-based checks, and acceptance criteria that can support both current delivery and future AI-assisted workflows.
Cross-Functional Collaboration
- Partner closely with Software Engineering, Product Management, UX, DevOps, and Customer Support teams.
- Participate in roadmap, release, flow planning, and architecture discussions to embed quality early and reduce late-cycle risk.
- Drive root cause analysis for production issues and implement preventative quality improvements.
- Help define acceptance criteria and ensure testability of new features.
- Encourage continuous feedback and quality ownership across engineering teams.
- Coach Product, UX, and Engineering partners on writing clear, testable acceptance criteria and risk statements that support automation, AI-assisted planning, and reliable delivery.
Technical Skills / Competencies
- Deep expertise with modern test automation frameworks including Playwright.
- Experience with UI, API, integration, regression, and end-to-end test automation.
- Experience integrating automated testing into GitLab CI/CD or similar DevOps platforms.
- Strong understanding of software architecture, REST APIs, microservices, and distributed systems.
- Experience with cloud platforms, preferably AWS.
- Familiarity with observability and monitoring tools such as CloudWatch, Grafana, Prometheus, or OpenTelemetry.
- Ability to use production telemetry, customer workflow data, and operational signals to guide risk-based testing and quality investment.
- Experience with performance (load), scalability, and resilience testing.
- Knowledge of test management, defect management, and quality reporting tools.
- Familiarity with AI-assisted development or testing tools such as Claude, GitHub Copilot, Cursor, CodeRabbit, GitLab Duo, or equivalent, and an ability to evaluate where these tools can safely improve quality workflows.
Education/Experience
- Bachelor’s degree in Computer Science, Software Engineering, or related technical field, or equivalent experience.
- 10+ years of experience in Software Testing or Quality Engineering.
- 3+ years of experience leading or managing software quality engineering teams.
- Proven experience building and scaling automation-first Quality Engineering organizations.
- Strong experience designing and implementing automated testing strategies for modern software applications.
- Experience leading Agile software development teams.
- Strong communication, coaching, and stakeholder management skills.
- Experience managing distributed or global engineering teams.
