Staff Software Engineer, Quality Engineering

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer, Quality Engineering based in United States.

This is a senior technical leadership role focused on defining and scaling a modern, AI-native approach to software quality across a growing SaaS organization. You will own the quality engineering strategy and expand an existing quality operating model across multiple product lines. The environment combines AI-assisted test generation, automated validation, human judgment, and evidence-based release governance. You will help make quality an integrated property of the engineering lifecycle rather than a final inspection step. Working closely with Product Engineering, Platform Engineering, DevOps, and Engineering leadership, you will influence architecture, developer practices, and release discipline. This role offers the opportunity to shape emerging approaches to agent-driven testing while directly improving reliability, delivery speed, and customer confidence.

Accountabilities:

• Own and evolve the quality engineering operating model, expanding established practices across multiple product lines while defining the technical vision, roadmap, and standards for quality.
• Lead the systems and workflows through which AI agents generate, maintain, and execute API, UI, integration, contract, performance, and end-to-end test coverage, ensuring human review keeps automated output trustworthy.
• Manage the test review and activation process, maintaining review throughput and ensuring test drafts move efficiently from creation to validated coverage.
• Establish and enforce evidence-based release governance, including release gates, explicit exit criteria, documented waivers, accountable sign-off, and escalation processes that remain effective under delivery pressure.
• Define which scenarios require human judgment and establish processes for progressively retiring manual tests as automation and AI capabilities improve.
• Build an evaluation framework for AI-driven quality, including golden verdict datasets, agent calibration, escape-rate analysis, and data-driven allocation of human review effort.
• Champion developer-owned quality by embedding automated testing, quality standards, and validation practices directly into software development and CI/CD workflows.
• Advance behavioral and exploratory validation through persona walkthroughs, exploratory charters, and judgment-based testing that verifies software behavior against customer and business intent.
• Partner with Engineering Managers, Staff Engineers, Product Engineering, Platform Engineering, and DevOps to improve reliability, maintainability, developer productivity, and release confidence.
• Mentor engineers and QA professionals through code reviews, technical design discussions, and pairing, while helping teams articulate defects and quality risks precisely enough to improve future AI-assisted capabilities.
• Define and monitor engineering quality metrics, including escape rates, AI verdict calibration, manual-test catalog trends, waiver frequency, and deployment success.
• Evaluate emerging testing technologies, agentic engineering practices, and AI-assisted development tools to continuously improve the organization's engineering capabilities.
• Serve as a technical thought leader and change agent, helping establish a culture where AI generates coverage, humans arbitrate evidence, and quality is engineered throughout the development lifecycle.

Requirements:

• 10+ years of experience in Software Engineering, Quality Engineering, SDET, or comparable technical roles, including leadership of quality initiatives across multiple engineering teams.
• Demonstrated experience designing or implementing AI-assisted or agentic quality workflows, such as AI-generated test coverage, computer-use testing, LLM evaluation and calibration, or comparable systems built around AI-generated output.
• Strong background designing modern automated testing systems for enterprise SaaS applications, with sound judgment around which quality activities should be automated and which require human expertise.
• Strong software engineering capabilities, including the ability to review and improve AI-generated code and tests; experience with Java and TypeScript is particularly valuable.
• Experience with evidence-based release governance, including release gates, exit criteria, waivers, sign-off accountability, and quality metrics.
• Deep understanding of distributed systems, cloud-native applications, CI/CD, microservices, and architectures designed for testability and reliability.
• Demonstrated technical leadership and mentoring experience, with the ability to influence engineering direction without relying solely on formal authority.
• Excellent written and verbal communication skills and the ability to collaborate effectively across multiple engineering and product teams.
• Passion for developer experience, engineering enablement, continuous improvement, and building quality into software development processes.
• Experience building or transforming a Quality Engineering organization within a high-growth SaaS environment is preferred.
• Previous experience as a Principal Engineer, Staff Engineer, Quality Engineering Architect, or senior SDET is advantageous.
• Experience delivering intelligent test generation, autonomous test maintenance, or production-grade agent-driven quality workflows is highly valued.
• Familiarity with automation technologies such as Playwright, Selenium, REST Assured, JUnit/TestNG, Cypress, or comparable frameworks.
• Experience with shift-left testing, developer-owned quality, testing-pyramid strategies, and engineering quality measurement.
• Familiarity with spec-driven or artifact-first development, executable contracts, scenario-level evidence, and test management systems such as Xray, Jira, or comparable platforms.
• Knowledge of Kubernetes, serverless architectures, cloud-native platforms, microservices testing, and observability practices is beneficial.
• Must qualify as a U.S. person under applicable federal law, including U.S. citizens, lawful permanent residents, asylees, or refugees, due to potential access to systems and data subject to U.S. critical infrastructure regulations.

Benefits:

• Competitive compensation package aligned with experience and expertise.
• Remote-first work environment designed to provide flexibility and work-life balance.
• Professional development opportunities, including training, mentorship, and career growth support.
• Comprehensive health, dental, and vision insurance beginning on day one.
• Short- and long-term disability coverage and basic life insurance at no cost to employees.
• 401(k) plan with a 4% employer match.
• Flexible paid time off and a supportive culture that values sustainable work practices.
• Opportunity to contribute to mission-driven technology supporting a more reliable, sustainable, and cost-efficient energy infrastructure.
• A lean, fast-moving environment that encourages bold thinking, transparency, continuous learning, and meaningful ownership.
• The opportunity to shape emerging AI-native engineering practices while influencing quality strategy across the organization.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.