Senior QA/SDET

Vouched

19h•$180,000 - $210,000•Remote

About The Position

Vouched is seeking a Senior QA/SDET to build quality into every release of its identity verification platform. The role owns quality across the product lifecycle, from reviewing requirements and designs through test planning, automation, release validation, and production verification. The engineer will build and maintain test frameworks, automated suites, and quality gates across APIs, web and mobile SDKs, and the customer dashboard, partnering with engineering, product, and machine learning stakeholders.

Requirements

At least 6 years of experience in software quality engineering, including at least 3 years as an SDET or test automation engineer in a software engineering organization.
Strong programming skills in at least one test automation language: TypeScript/JavaScript, Python, Java, Kotlin, or Swift; ability to write clean, maintainable test code.
Hands-on experience building and scaling web UI and API test automation frameworks, using tools such as Playwright, Cypress, WebdriverIO, Selenium, Jest, or Postman.
Experience testing iOS and Android applications or SDKs, using tools such as Appium, XCUITest, or Espresso, including real-device clouds such as BrowserStack or Sauce Labs.
Experience integrating tests into CI/CD pipelines such as GitHub Actions or CircleCI and working with containerized and cloud environments; Docker experience and GCP familiarity are preferred.
Experience with performance and load testing tools such as k6, Gatling, or JMeter, and observability tools such as Datadog or equivalent.
Solid understanding of security and privacy testing, including authentication and authorization, OWASP Top 10, input validation, and safe PII handling in test environments.
Experience in regulated environments and supporting compliance frameworks such as SOC 2, ISO 27001, GDPR, or HIPAA, including test evidence and audit readiness.
Proficiency with AI-powered development tools such as Claude Code, Cursor, or GitHub Copilot, with demonstrated ability to accelerate test development.
Strong debugging and root-cause analysis skills across client, API, and database layers.
Excellent written and verbal communication skills, including the ability to write clear test plans, bug reports, and quality reports.
Experience working in a startup environment.
Experience managing or collaborating with distributed teams.
Must be based in the United States and have US work authorization.

Nice To Haves

Familiarity with identity verification, computer vision, or AI/ML-based solutions, or experience testing ML model quality.
HIPAA compliance experience.
GCP experience.

Responsibilities

Define and own the platform test strategy across unit, integration, API, end-to-end, and exploratory testing.
Design, build, and maintain scalable test automation frameworks for REST APIs, the web capture SDK, iOS and Android SDKs, and the customer dashboard.
Integrate automated tests into CI/CD pipelines as fast, reliable quality gates and reduce flaky tests.
Validate identity verification flows across devices, browsers, cameras, and network conditions, including document capture, selfie and liveness checks, and webhook delivery.
Build and maintain safe synthetic test data for identity documents, selfies, and identity records without using real personal data.
Test security and privacy controls, including authentication, authorization, input validation, PII handling and redaction, and data retention; partner with security on vulnerability findings.
Produce traceable test evidence and change-validation records to support compliance readiness.
Conduct performance, load, and reliability testing of APIs and processing pipelines.
Partner with ML engineers to validate model and pipeline changes using regression datasets and accuracy benchmarks.
Own release validation and sign-off; triage, reproduce, and investigate defects, including customer-reported production issues, and add escaped bugs to automated coverage.
Define and report quality metrics, including defect escape rate, automation coverage, flakiness, and time-to-detect, and use them to drive continuous improvement.
Use AI-powered tools to accelerate test creation, test data generation, and failure triage.
Promote quality across engineering by reviewing designs and pull requests for testability and mentoring engineers on testing practices.
Evaluate and adopt AI-powered tools and workflows to improve test speed, coverage, and reliability.