Software Quality Engineer

Zipliens is a leading lien resolution company that specializes in streamlining the lien process for personal injury law firms. Our work helps law firms operate more efficiently and helps the injured people they serve access settlement funds more quickly and accurately. We are looking for a quality engineer who is passionate about building the testing and evaluation that keeps complex, data-heavy products working correctly at scale.

Zipliens is looking for a Quality Engineer to join our team and own quality for a product area within the applications we build for the legal industry. After several years of high growth, Zipliens has become a leader in lien resolution, a process required in most personal injury settlements. The software we build supports that work, so the quality of what we ship has a clear, real-world impact on law firms and the people they represent.

We're scaling engineering significantly this year, and quality engineering is growing along with it. QA at Zipliens is embedded in the engineering teams and combines exploratory testing with automation. You'd own quality for a feature or product area, including the test strategy, the automation behind it, and the release sign-off for that area. You'll have established patterns and existing test suites to work from, and you'll help improve them as the team grows.

We also build with AI as a first-class part of the workflow, and that applies to testing as much as to development. Our product uses LLMs to extract structure from medical records and lien correspondence, so evaluating non-deterministic output is a regular part of the job. We also use agentic coding tools and internal skills and harnesses we've written ourselves to build and maintain automation, and you'd be expected to use those tools well, review what they produce, and help improve them.

• 3+ years on a QA or software development team, including experience owning test coverage for a feature or product area.
• Strong skills in at least one of exploratory testing and test design, test automation and infrastructure, or AI/LLM evaluation, with working proficiency in a second. We don't expect the same depth in all three.
• Hands-on experience building and maintaining automated test suites in a modern framework (Playwright, Cypress, pytest, or similar), including diagnosing flaky tests and fixing their root causes.
• Comfortable reading and writing code. Our backend is Python/Django and our frontend is React, and you should be able to read a change in either and understand what it affects and what it puts at risk.
• Experience integrating tests into CI pipelines and deciding which checks should gate a merge or a deploy.
• Strong SQL. Much of what we test lives in PostgreSQL, and verifying a workflow often means verifying the data it produced as well as what the UI shows.
• Hands-on experience testing LLM or ML features, whether in production or through prototypes and experimentation: building golden datasets, measuring output quality, and understanding how these systems fail.
• Experience using or experimenting with agentic coding tools, and good judgment about when their output needs a closer look.
• Clear written communication. You'll be writing defect reports, test plans, and release sign-offs for engineers and product, and explaining risk to non-technical stakeholders.

• →Own quality for a feature or product area, including the risk-based test strategy, the regression scope, and the release sign-off for that area.
• →Build and maintain the automated test suites for your area and keep them integrated with CI. When tests fail or become flaky, you'll troubleshoot them and fix the underlying cause.
• →Run exploratory testing against the lien workflow and develop a detailed understanding of the applications your team owns, including their risk areas and failure modes.
• →Test our LLM-based features. This includes building the evaluation suite for a feature, setting acceptance thresholds with product (for example, precision and recall targets for extraction), checking LLM-judge agreement against human labels, and adding adversarial and prompt-injection cases.
• →Use agentic coding tools to build and maintain automation, and review AI-generated tests before they merge.
• →Join refinement early enough to shape Acceptance Criteria with the Product Owner, flag testability gaps before development starts, and recommend coverage and risk priorities for your area.
• →Shepherd defects for your area from triage through resolution, writing clear, reproducible reports that engineers can act on.
• →Work directly with the engineers on your team day to day. QA at Zipliens is embedded in the engineering teams rather than run as a separate function.

• Experience testing document processing or extraction from unstructured data.
• Experience testing third-party integrations, especially where the counterparty's documentation isn't solid and you need contract tests, sandboxes, or recorded fixtures to work around it.
• Familiarity with AWS and Kubernetes. We have an SRE who owns the cluster - you won't be running it, but you'll be reading logs and working out where a failure happened in it.
• Experience handling sensitive data such as PHI, or working under HIPAA-style requirements.