THE TEAM:
At Kind Lending, our family of diverse and talented Kind Ambassadors are the driving force behind our new approach to the mortgage experience. They're the heart and soul of the organization and our "People Before Profits" mentality shines through in every department. Kind Lending is growing and is looking for top mortgage professionals who value opportunity, lasting business partnerships, and who live out our KIND mindset. Kind Lending is determined to provide the best service in the industry while also providing homebuyers with a great selection of products to enhance their buying experience. Backed by our trusted leadership team, Kind Lending's friendly and professional model puts the “fun” in funding.
Position Summary:
Kind Lending is automating the loan lifecycle — re-pricing, re-disclosures, broker-initiated change requests, automated underwriting and condition clearing, CD and closing doc automation. Every one of those features touches a regulated, money-moving workflow, and today they are verified largely by manual UAT from Ops and Sales. As our Senior SDET, you will build the automated test infrastructure that lets pilots expand safely and releases ship faster — including the harder problem of testing AI-driven decisioning, where outputs are non-deterministic and the cost of a wrong answer is a compliance event.
Responsibilities:
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Design and own the test automation strategy across the platform: API/integration tests against the LOS (Blue Sage) and broker portal (Kwikie), end-to-end tests for pilot workflows (COC, re-disclosures, Gateless condition clearing), and regression suites that run in CI/CD.
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Build test frameworks and tooling other developers actually use — fixtures, synthetic loan files, environment seeding, and contract tests for third-party integrations (Gateless, Cotality, AUS, pricing).
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Develop evaluation harnesses for AI/LLM features: golden datasets, eval suites, regression detection for prompt and model changes, and pass/fail gates on automated underwriting outputs.
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Convert today's manual UAT knowledge (Ops and Sales test scripts) into automated coverage, and partner with UAT testers so human inspection focuses where it adds the most value.
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Define quality gates for pilot expansion — what must be green before a feature rolls from pilot group to all brokers — and instrument production monitoring to catch escapes early.
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Verify compliance-critical behavior: disclosure timing, fee tolerances, audit trails, and data integrity across systems.
AI-Assisted Development (Required):
Kind Lending's technology team builds AI-first. This is not a preference; it is how the team works every day. To be considered, you must:
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Use AI coding tools daily (e.g., Claude Code, GitHub Copilot, Cursor, or equivalent) as a core part of your workflow — not as an occasional autocomplete.
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Demonstrate the ability to decompose work into well-structured prompts and agentic tasks, then critically review, test, and harden AI-generated code before it ships.
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Show measurable productivity gains from AI-assisted development (be prepared to walk through real examples in the interview, including a live AI-paired coding exercise).
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Maintain sound judgment about where AI accelerates work and where human review is mandatory, especially in a regulated lending environment.
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Use AI agents to generate, maintain, and triage tests at scale — and build evals that hold AI-generated product code to the same bar as human-written code.
Qualifications:
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6+ years in software engineering with at least 4 focused on test automation/SDET work; strong coding skills in at least one of TypeScript/JavaScript, Python, Java, or C#.
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Proven experience building test frameworks from scratch — API testing (Postman/REST-assured/pytest/supertest), UI/E2E (Playwright or Cypress), and CI/CD integration (GitHub Actions, GitLab CI, Jenkins, or Azure DevOps).
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Experience testing complex, multi-system integrations with third-party services, including mocking, contract testing, and test data management.
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Daily, demonstrable use of AI coding tools — see AI-Assisted Development above. This requirement is absolute.
Preferred Qualifications:
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Mortgage technology experience strongly preferred: LOS platforms (Blue Sage, Encompass), broker portals, AUS (DU/LP), disclosure/doc systems, or other regulated fintech where TRID-style timing and tolerance rules apply.
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Experience evaluating LLM or ML systems in production — eval frameworks, golden sets, non-deterministic output testing, or model regression gates.
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Performance and load testing experience for event-driven/queue-based architectures.
Pay Disclosure:
The starting base pay for this position is $125k/annually. The actual base is dependent on many factors such as: work experience, business needs, market demands, and other compensation components. The base pay range is subject to change and may be modified in the future.
Disclaimer Statement:
This job description is not intended, nor should it be construed to be an exhaustive list of all responsibilities, duties, skills, or working conditions associated with a job. It is intended to be a general description of the principal requirements common to positions of this type.
Work Authorization:
Must be able to verify identity and employment eligibility to work in the U.S. without a visa sponsorship.
Other Duties:
This job profile is not intended to be an all-inclusive list of job duties and responsibilities, as one may perform additional related duties as assigned to meet the needs of the organization.
Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Must be able to lift up to ten pounds. Primary functions require sufficient physical ability and mobility to work in an office setting; to stand or sit for prolonged periods of time; to occasionally stoop, bend, kneel, crouch, reach, and twist; to lift, carry, push, and/or pull light to moderate amounts of weight; to operate office equipment requiring repetitive hand movement and fine coordination including use of a keyboard; and to verbally communicate to exchange information. VISION: See in the normal visual range with or without correction. HEARING: Hear in the normal audio range with or without correction.
Kind Lending is an Equal Opportunity Employer committed to workforce diversity. Qualified applicants will receive consideration without regard to race, religion, creed, color, orientation, gender, age, national origin, veteran status, disability status, marital status, sexual orientation, gender identity, or gender expression.
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