Kinective
Automation Engineer
Golden, CO
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hirly's read of this role
- Seniority
- Mid level
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 3 Oct 2026
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the posting
Description
Lead the Way to Intelligent Banking with Us!
You might not think about what happens behind the scenes when you check your bank balance or deposit a check from your phone, but we do. Every day.
Kinective empowers banks and credit unions to move beyond keeping up with technology to shaping the future of banking. Our platform seamlessly connects the right tools, delivers real-time data, and drives smarter operations for more than 4,000 financial institutions nationwide. We are a fast-growing team built on individual ownership, company-wide collaboration, and setting industry-leading standards. Here, new ideas are encouraged, candid feedback is welcomed, and your growth truly matters as much as the company’s. At Kinective, we are leading the way to intelligent banking together and enjoying the journey along the way.
Why This Role Matters
As a Manual Test & Automation Engineer at Kinective, you’ll play a key role in ensuring our products are reliable, scalable, and ready for real-world banking environments. You’ll own quality engineering for assigned product areas while contributing to both hands-on manual testing and automation efforts, helping strengthen release confidence, AI-assisted testing, and technical quality practices across the Data Intelligence platform.
This role goes beyond test execution—you’ll translate requirements into thoughtful test strategies, perform manual testing as needed, build maintainable UI and API automation, design and govern AI-assisted QA workflows, improve framework and pipeline health, make risk visible, and partner with Product and Engineering to deliver with confidence. If you enjoy digging into complex problems, improving how things work, and building software customers can trust, you’ll thrive here. You'll work primarily in a data-heavy enterprise platform with a mature, component-framework-based UI — dynamic grids, embedded frames, and heavy asynchronous loading. Building automation that stays stable against it is genuinely challenging work, and genuinely valuable when it's done well.
What you’ll own
Test Strategy & Planning
- Own risk-based test strategy for assigned product areas, translating requirements and acceptance criteria into clear, testable outcomes.
- Drive coverage planning across scenarios, test data, environments, and release risks in partnership with QA, Product, and Engineering.
- Use AI-assisted story analysis to accelerate test design while ensuring human review, traceability, and quality standards.
Test Execution & Automation
- Perform manual functional, regression, exploratory, and scenario-based testing as needed to validate product quality and release readiness.
- Own reliable UI and API automation for critical workflows using Playwright, TypeScript, and maintainable test patterns.
- Run and report release-scoped regression, producing clear readiness evidence and a documented view of coverage gaps before a release.
- Build reusable page objects, components, utilities, fixtures, test data, assertions, and diagnostics that improve speed and trust.
- Apply AI-assisted tools to generate, extend, debug, and maintain tests while validating correctness, security, determinism, and release relevance.
- Manage test environments and test data, including provisioning and refreshing environments, loading and validating datasets, and troubleshooting remote access and connectivity issues.
Defect Management & Troubleshooting
- Triage the scheduled regression run on a daily cadence, classifying each failure by disposition — product defect, test defect, environment issue, or inconclusive — and driving each to a resolution or an owner.
- Own clear defect identification, documentation, triage, and prioritization in Jira through resolution.
- Diagnose root causes across application, test, data, environment, and infrastructure issues using evidence-driven analysis.
- Turn escaped defects and production incidents into durable regression coverage or a documented improvement plan.
Collaboration & Continuous Improvement
- Own quality visibility across the SDLC by surfacing regression trends, flaky-test patterns, framework health, CI/CD feedback, and release evidence.
- Maintain QA documentation, test cases, and knowledge-sharing resources.
- Own Jira/Xray test-management upkeep on a per-story basis: creating Test issues, linking Test Executions back to Stories, and keeping automation-to-test-key mappings current so traceability stays intact.
- Use and maintain the team's AI-assisted QA workflows, applying judgment about when generated output can be trusted and when it needs rework.
- Partner across teams, review test code, mentor others, and raise quality standards through shared ownership and practical improvements.
How We’ll Measure Success
- High-quality releases with reliable evidence and minimal critical defects reaching production.
- Strong risk-based coverage, including effective automation that improves speed, confidence, and repeatability.
- Efficient defect resolution and a trustworthy regression suite, with clear documentation, root-cause identification, stable pass rates, a shrinking backlog of non-actionable failures, and results the team acts on rather than works around.
- AI-assisted QA workflows improve speed and coverage while producing standards-compliant, maintainable, reviewable, and traceable outputs.
- Early detection of issues through stronger requirements, testability, collaboration, and feedback loops.
- Ongoing improvements to QA processes, framework health, pipeline feedback, and release readiness.
- Effective collaboration and mentoring, with growth toward broader QA leadership responsibilities over time.
Success here isn’t about checking boxes – it’s about propelling Kinective’s mission to lead the way to intelligent banking. You must bring excellence to your craft, balance resourcefulness with respect, share and celebrate unique expertise and diverse perspectives, and continuously raise the bar as we innovate and grow.
Necessary Qualifications & Competencies
- 4+ years in Quality Assurance, Quality Engineering, manual testing, automation engineering, or a similar role.
- 2+ years designing and maintaining test automation for UI, API, and regression coverage.
- Practical experience using AI-assisted tools in QA or software engineering workflows, including test design, code generation, debugging, failure analysis, or documentation.
- Experience working as a senior individual contributor, technical owner, or mentor in a quality engineering team.
Technical Skills
- Hands-on experience with Playwright and TypeScript or a comparable modern browser-automation framework.
- Ability to evaluate AI-generated outputs for correctness, maintainability, traceability, security, deterministic behavior, and fit-for-purpose coverage.
- Experience with API testing tools such as REST Assured, Postman, or similar.
- Working knowledge of SQL, APIs, GitLab, pull requests, code review, CI/CD pipelines, Jira, Xray, and system integrations.
Process & Tools
- Strong understanding of SDLC, STLC, Agile delivery, risk-based testing, and shift-left quality practices.
- Ability to design maintainable automation using page objects, reusable components, stable locators, meaningful assertions, and useful diagnostics.
- Ability to analyze logs, traces, screenshots, AI-generated explanations, and test artifacts to identify root cause and improve test signal.
Core Competencies
- Strong analytical and problem-solving skills with high attention to detail and sound judgment when using AI-generated recommendations.
- Clear documentation, communication, and stakeholder-management skills, including the ability to explain AI-assisted QA decisions and tradeoffs.
- Self-motivated, adaptable, collaborative, and comfortable influencing responsible AI adoption without formal authority.
Preferred Skills
Familiarity with Selenium/WebDriver and Java-based legacy automation is a plus, but not require
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