Staff QA Engineer

Syllo

2h•$170,000 - $210,000•Remote

About The Position

Syllo is seeking a Lead QA Engineer to take ownership of and advance the company's quality assurance function. This role is highly autonomous and hands-on, requiring the individual to define the quality strategy, drive automation initiatives, and ensure all releases meet high standards for reliability, performance, and user experience. The ideal candidate will possess deep technical expertise combined with strong product instincts, understanding customer needs, anticipating potential issues, and building scalable systems to support confident software releases. The role involves setting technical direction for Product Operations, establishing testing frameworks and processes, promoting quality across Engineering, Product, and Customer Success, and utilizing AI to innovate testing methodologies. The Lead QA Engineer will have the autonomy to select tooling, introduce new technologies, and continuously enhance the software development and release process.

Requirements

7+ years of experience in Software Quality Assurance with significant experience in automation.
Experience owning QA with a high degree of autonomy in a fast-paced software organization.
Proven ability to design and implement scalable QA processes and automation strategies.
Strong product instincts with the ability to understand complex workflows and advocate for an exceptional user experience.
Experience driving quality across cross-functional teams.
Strong experience with modern automation frameworks such as Playwright, Cypress, or Selenium.
Experience testing AI or LLM-powered products.
Experience building or significantly evolving a QA function in a growing startup.
Proficiency in programming languages.
Experience integrating automated testing into CI/CD pipelines using tools such as GitHub Actions, GitLab CI, or Jenkins.
Experience with API, integration, regression, and end-to-end testing.
Familiarity with modern bug tracking and test management tools.
Experience implementing AI-assisted testing workflows.

Responsibilities

Own and evolve Syllo's overall quality assurance strategy.
Establish scalable QA processes that support rapid, high-confidence releases.
Define quality standards, release criteria, and testing best practices across the organization.
Continuously improve how quality is measured, communicated, and maintained.
Identify opportunities to shift quality earlier in the development lifecycle through better tooling, automation, and process.
Set the technical direction for our automated testing strategy.
Design, build, and maintain automated testing frameworks that integrate seamlessly into our CI/CD pipeline.
Evaluate and implement the tools, frameworks, and architecture that best support long-term quality and engineering velocity.
Continuously expand automated test coverage while reducing manual testing effort.
Drive the evolution of our automation capabilities as our product and engineering organization scales.
Develop a deep understanding of customer workflows, product functionality, and business priorities.
Think like a customer, proactively identifying edge cases, failure modes, and usability issues before they reach production.
Distinguish true release blockers from lower-priority defects, balancing quality with execution speed.
Partner with Product to recommend improvements that enhance the customer experience, not just eliminate bugs.
Champion quality across Engineering, Product, Customer Success, Product Operations, and other cross-functional partners.
Coordinate testing efforts across teams while maintaining clear ownership and accountability.
Partner with Customer Success to reproduce complex customer issues, translate them into actionable test cases, and validate fixes before release.
Influence engineering and product teams to continuously improve quality throughout the software development lifecycle.
Evaluate and implement AI-powered workflows that improve testing efficiency, including generating test cases, maintaining automation, accelerating exploratory testing, analyzing failures, identifying regression risk, and increasing release confidence.