Staff QA Engineer I

Paid holidays and flexible, take-it-as-you-need-it scheduled time off

A culture built on innovation that values big ideas, no matter where they come from

A MacBook set up and ready from day one, plus a $500 stipend to design your ideal workspace

Equity in a rapidly growing startup backed by top-tier VCs

TO BE CONSIDERED FOR THIS ROLE, PLEASE SUBMIT AN UPDATED RESUME TRANSLATED TO ENGLISH

Role Overview

As a Staff QA Engineer I, you contribute to the quality assurance process by developing and executing both manual and automated tests to ensure our software meets the highest quality standards. You work closely with development teams to identify, reproduce, and document bugs, while also designing robust test plans and strategies to ensure product reliability. Your expertise in testing methodologies helps guide the team in adopting best practices, and you act as a mentor for junior engineers, helping them grow their testing skills.

Our team is passionate, empathetic, hard working, and above all else focused on improving the lives of our service professionals (our Pros). Our success is their success.

What you do each day:

Lead AI adoption and operationalization across the squad. Design AI-enhanced testing workflows, measure impact with evidence, and continuously improving quality and efficiency

Define standards for the safe, reliable use of AI within test pipelines, regression systems, and validation workflows while measuring return on investment (ROI) through accuracy, defect detection, regression stability, coverage gains, and operational efficiency

Design and govern agentic testing workflows using Model Context Protocol (MCP) technologies (i.e. Maestro MCP, Playwright MCP) across multiple teams

Evaluate emerging AI and agentic testing technologies and lead root-cause analysis when workflows degrade through false positives, regression drift, unstable automation, or other quality issues

Partner with machine learning operations (MLOps), platform, Product, and Engineering teams to establish evaluation standards, production quality baselines, and scalable validation strategies

Design advanced test strategies, plans, and machine-readable test cases that enable AI-assisted automated test generation and strengthen coverage for new features and complex product changes

Establish and continuously improve quality assurance methodologies, automated testing frameworks, and technical standards that influence quality practices across Engineering

Collaborate with Product and Engineering leaders to refine requirements, identify quality risks, and ensure comprehensive test coverage throughout the software development lifecycle

Mentor quality assurance and engineering professionals in advanced testing techniques, AI-assisted quality practices, and scalable automation approaches

Communicate quality insights, testing outcomes, technical risks, and recommendations clearly to Engineering leaders and cross-functional stakeholders

Qualifications:

8+ years of experience in quality assurance engineering, with a focus on both manual and automated testing

Proficiency in automated testing frameworks (i.e. Playwright, Cypress, TestNG, JUnit)

Experience with continuous integration/continuous delivery tools (i.e. Gitlab, CircleCI)

Demonstrated experience operationalizing AI-assisted and agentic testing workflows across a team, defining validation standards, safe delegation and human-in-the-loop boundaries, and tracking measurable outcomes (AI ROI)

Hands-on experience with AI-assisted testing and MCP-based test generation/execution (Maestro MCP, Playwright MCP), with judgment about where AI output is reliable vs. where it needs tighter validation

Experience working with bug tracking and test management tools (i.e. JIRA, TestRail)

Bachelor’s degree in Computer Science, Engineering, or equivalent work experience

Proven experience driving team efficiency or output quality through the strategic use of AI tools and automation

What will help you succeed:

A multi-dimensional background with a breadth of cross-functional interests or depth of specialized mastery

A track record of embedding AI knowledge-sharing into team culture — coaching Senior engineers on the shift from personal AI productivity to squad-level operational impact

A habit of building reusable AI operational assets (prompt libraries, validation checklists, triage runbooks, agentic playbooks)

Personal resilience to learn from scratch, and successfully thrive in ambiguity

Strong problem-solving and analytical skills

Ability to work in a fast-paced, collaborative environment

Excellent communication skills, both written and verbal

High attention to detail and commitment to delivering high-quality work

Proactive in identifying areas for improvement and suggesting solutions

Compensation starts at $6,400 USD per month.