QE Automation Lead
Kapitus · Virginia, Maryland, Washington DC-, United States
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Kapitus has helped small and midsize businesses access capital for two decades, funding roughly $2 billion to date and building toward $6 billion and beyond. We originate, decision, fund, and service financing every day across a growing set of products and partner channels. As we scale, we are investing in the technology and quality foundation that growth depends on.
We are standing up a modern quality-engineering practice built on automated regression, and we are hiring a hands-on QE Automation Lead to own the strategy, the framework, and the team that delivers it. You will set the automation standards, architect and govern the framework, mentor the engineers, and make release readiness measurable, in close partnership with Product, Development, DevOps, and Architecture. You will also lead the shift from a largely manual regression model to reliable, pipeline-gated automation, the change that lets Kapitus release faster with higher confidence.
What You Will Do:
- Lead the strategy. Own the automation strategy and technical direction across multiple QE teams, products, and delivery streams.
- Partner across the org. Align quality priorities, delivery risks, and release-readiness expectations with Product, Development, DevOps, Architecture, and Leadership.
- Build and govern the framework. Design, evolve, and govern scalable automation frameworks and reusable components using Playwright with TypeScript.
- Set the standards. Establish automation standards for test design, code quality, reviews, branching, test data, maintainability, reporting, and framework adoption.
- Stay hands-on. Develop, review, debug, and optimize automated tests across UI, API, integration, end-to-end, and data-validation layers.
- Wire quality into CI/CD. Integrate automated tests and quality gates into CI/CD pipelines for fast, reliable feedback across the delivery lifecycle, and move toward automation in the Definition of Done.
- Make quality measurable. Define and report actionable quality and automation metrics: coverage, pass rate, defect trends, escape rate, flaky-test rate, execution time, and automation effectiveness.
- Prioritize by risk. Use data and risk-based analysis to prioritize automation investment, identify quality gaps, and communicate product risk and release readiness to technical and non-technical stakeholders.
- Lead root-cause analysis. Lead root-cause analysis for complex failures and recurring defects, separating application, environment, test-data, integration, and automation issues.
- Mentor and grow the team. Guide, review, pair with, and grow the QE engineers, raising engineering standards across the team.
- Coordinate distributed delivery. Coordinate work across distributed teams, remove roadblocks, and drive consistent execution and accountability.
- Champion shift-left quality. Improve story testability, acceptance criteria, test planning, and in-sprint automation so quality moves earlier.
- Lead the shift to automation. Lead the transition from manual regression to automated regression, retiring manual effort as automated coverage proves out and runs green in CI, and capturing manual test cases into automation as you go.
- Govern new and AI-assisted tooling. Evaluate emerging tools and AI-assisted testing approaches, applying governance and quality controls before adoption.
- Stay current. Track fintech trends, regulatory considerations, cloud technologies, and modern quality-engineering practices.
What We’re Looking For:
- 8+ years experience in software quality engineering, including three or more leading automation initiatives or providing technical leadership across multiple teams.
- Proven ability to lead, influence, and align distributed QE teams without relying solely on direct reporting relationships.
- Advanced hands-on experience designing, coding, debugging, and reviewing automation using Playwright with TypeScript or comparable modern technologies.
- Demonstrated success building scalable automation frameworks and reusable libraries across UI, API, integration, end-to-end, and data layers.
- Strong grasp of software architecture, object-oriented programming, test design patterns, clean code, and maintainable automation practices.
- Experience integrating automation with CI/CD platforms and implementing quality gates, parallel execution, cross-browser coverage, reporting, and failure diagnostics.
- Experience defining and communicating quality KPIs and using metrics to drive decisions, prioritization, and continuous improvement.
- Strong knowledge of API testing, test-data management, backend validation, SQL, and service-integration testing.
- Experience testing Salesforce solutions and full-stack applications across UI, API, integration, and data layers.
- Proven mentoring, coaching, and technical-review skills that raise engineering standards across teams.
- Excellent executive-level communication and stakeholder management, including presenting quality status, risks, tradeoffs, and recommendations clearly.
- Strong analytical, problem-solving, prioritization, and decision-making skills in complex delivery environments.
- Solid command of Agile and Scrum, DevOps, shift-left testing, risk-based testing, and the full software development lifecycle.
- Experience with Jira, Confluence, Zephyr Scale, Git-based workflows, and modern CI/CD tooling.
- Experience in financial services, regulated environments, or high-availability platforms is strongly preferred.
- Automation leadership: strategy, framework governance, coding standards, code reviews, mentoring, and cross-team adoption.
- Automation framework: advanced Playwright and TypeScript, including reusable fixtures, page and component models, parallel execution, cross-browser testing, tracing, and reporting.
- Test coverage: functional, regression, API, integration, end-to-end, contract, and data-validation automation.
- Application platforms: Salesforce and full-stack applications across front-end, back-end, API, integration, and data layers.
- API and data testing: Postman, Swagger and OpenAPI, REST and JSON, SQL, and backend validation.
- CI/CD and source control: GitHub or Bitbucket, pull-request workflows, and pipeline integration using Jenkins, GitHub Actions, Azure DevOps, or comparable tools.
- Quality metrics: automation coverage, pass rate, flaky-test rate, defect trends, escaped defects, execution duration, and release-readiness reporting.
- Test management and collaboration: Jira, Confluence, and Zephyr Scale.
- Working knowledge of security, accessibility, and performance testing principles
Nice to Have:
- Additional languages and tools: Python, JavaScript, SQL, Java, Selenium, Cypress, Pytest, Rest Assured, or Cucumber.
- AWS services, containerized test execution, cloud-based test environments, and observability platforms.
- Performance testing with JMeter or k6, and accessibility testing standards and tools.
- Migrating legacy automation suites to Playwright or consolidating multiple framewo