Why This Job is Featured on The SaaS Jobs
Quality leadership is increasingly central in enterprise SaaS, especially for platforms that blend microservices with AI-driven workflows. This role stands out because it treats QA as a cross-functional operating system spanning platform engineering, customer-facing implementation work, and data science. In an agentic AI customer experience product, quality is not only release gating but also model behavior, data integrity, and reliability in production across many client configurations.
For a SaaS career, the remit offers durable leverage: building quality strategy that scales with CI/CD, defining measurable readiness signals, and making quality observable after deployment. The inclusion of security and compliance-oriented testing alongside performance and reliability aligns with how mature B2B SaaS teams reduce enterprise risk. The emphasis on AI and data validation also maps to a growing industry need for repeatable approaches to model accuracy, drift, and governance.
This is best suited to senior QA leaders who prefer influencing across engineering, product, and customer delivery rather than owning a narrow test function. It fits professionals comfortable balancing hands-on automation and tooling choices with executive-level prioritization, and those motivated by the ambiguity of setting standards for AI-centric SaaS systems.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Company:
Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences.
Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!
We’re seeking a Head of Quality Assurance (QA) to lead the organization’s quality charter across all engineering and customer-facing functions — Platform Engineering, Customer Success Engineering, Data Science, and AI Research. This role will define and drive the end-to-end quality vision for an AI-driven SaaS platform, ensuring that Netomi’s products meet the highest standards of functionality, performance, reliability, and security.
This leader will establish a center of excellence for Quality, embedding QA thinking across teams — from functional, non-functional, performance, and security testing to data validation and model accuracy testing — while cultivating a culture of continuous improvement and automation-driven efficiency.
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Responsibilities:- Quality Strategy and Leadership -
- Define and execute the Quality Engineering vision and roadmap aligned with organizational goals.
- Build and lead a multi-disciplinary QA team (Platform QA, Data Quality, Automation, and Performance Engineering).
- Partner with engineering, product, and customer success leaders to ensure quality is embedded across the SDLC.
- Establish quality KPIs and dashboards for visibility into release readiness, product stability, and production health.
- End-to-End Quality Ownership -
- Own functional and regression testing strategy across microservices, SDKs, APIs, and UI layers.
- Drive non-functional testing excellence — performance, scalability, reliability, failover, and compatibility.
- Lead security testing initiatives, collaborating with DevSecOps and compliance teams to ensure adherence to ISO, SOC 2, and GDPR standards.
- Introduce AI-augmented testing frameworks leveraging machine learning for predictive defect detection and data drift analysis.
- Data Science and AI Quality -
- Partner with the Data Science org to establish data quality pipelines for training and inference data.
- Define testing standards for AI model accuracy, precision, bias, and drift monitoring.
- Ensure data-driven validation frameworks are integrated into MLOps and deployment cycles.
- Customer Success Engineering Quality -
- Oversee QA processes for custom deployments, integrations, and client-specific configurations.
- Build automation frameworks to validate end-to-end customer experience workflows and integrations (Genesys, Salesforce, Zendesk, etc.).
- Process and Tooling Excellence -
- Institutionalize CI/CD-driven test automation for faster and safer deployments.
- Evaluate and implement next-gen QA tools for test management, performance benchmarking, and observability.
- Drive shift-left testing culture and early defect detection through static analysis, contract testing, and chaos testing.
- Foster collaboration between QA, DevOps, and Observability teams for quality-in-production metrics.
Requirements:- 10+ years of experience in software quality engineering, with 3+ years leading QA teams in a SaaS or platform environment.
- Proven experience in AI/ML or data-centric product quality, including validation of data pipelines and ML models.
- Deep understanding of microservices architecture, cloud platforms (AWS/Azure), and CI/CD pipelines.
- Hands-on experience with automation frameworks (Selenium, Cypress, Playwright, TestNG, PyTest, etc.).
- Expertise in performance testing tools (JMeter, Gatling, Locust) and security testing (OWASP, Burp Suite, ZAP).
- Strong grasp of API and SDK testing, ideally for multi-platform environments (web, mobile, voice).
- Exceptional communication, leadership, and stakeholder management skills with an ability to influence across functions.
- Preferred Skills
- Experience in AI/ML testing, data validation, and model governance frameworks.
- Familiarity with observability stacks (ELK, Grafana, Datadog, OpenTelemetry) for production monitoring.
- Understanding of GenAI systems, prompt testing, and retrieval-augmented generation (RAG) validation.
- Exposure to B2B enterprise platforms and multi-tenant SaaS architectures.
- Knowledge of secure SDLC and compliance frameworks (SOC 2, ISO 27001).
Why Netomi- Work at the frontier of AI-driven customer experience.
- Influence quality strategy across platform, AI, and customer success ecosystems.
- Collaborate with top-tier engineers and data scientists in a high-growth, innovation-driven culture.
- Competitive compensation, fast career progression, and global exposure.
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Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
