Head of QA Engineering

Our Product and Engineering team runs four platforms: SPARK (our AI platform for TPA operations), AGL (Advisor Growth Lab, our advisor community), Nexus Bridge (our systems integration layer), and Strongpay (our payroll and HR platform for small and mid-sized businesses, with thousands of logins every weekday). All four ship at the end of every two-week sprint.

Our engineers maintain unit and integration test suites and run them before every release. Beyond that, testing has largely been handled by whoever built the feature or requested it. That approach worked while the audience was small.

As Strongpoint grows, every firm we acquire moves onto the same platforms. In 2027, we are pushing for deeper adoption within each TPA, with these applications increasingly embedded in their core workflows. When a TPA runs its core work on our software, a bad release can disrupt client service. On Strongpay, it can disrupt payroll processing.

You will be our first dedicated Quality Assurance (QA) hire and will lead the function end to end. You will set the test plan, build the automation, determine what gates a release, and establish how we measure and report on quality.

There is no existing QA team to inherit, so coverage will come first from automation—including AI agents—before it comes from additional headcount.

Observe several release cycles and document where testing happens today across each platform and who performs it. Take ownership of the AI testing agents and begin logging escaped defects to establish a baseline.

Deliver the first automated regression suite for one high-traffic area of SPARK, AGL, or Strongpay.

Establish automated coverage across the core release paths of SPARK and AGL, with a coverage baseline for Strongpay beginning with payroll-critical paths.

The AI testing agents operate according to a written plan defining what they cover and what requires human review. A documented rollback plan has been used or rehearsed at least once. Baseline load-test results exist for SPARK and AGL.

A first version of the quality dashboard is live, reporting escaped defects and time to fix by platform.

A single dashboard reports key quality metrics across all four platforms, including escaped defects, time to fix, hotfix rate, automated coverage, and load-test results. Metrics are trended release over release and reviewed each sprint.

Strongpay and Nexus Bridge are tested to the same standard as SPARK and AGL, including load testing, and security testing is a standard step in every release.

• TypeScript throughout

• AGL uses Next.js and React

• SQL Server

• Hosted on Amazon Web Services (AWS) and Vercel

• Deployed with GitHub Actions

• Unit and integration testing with Jest and Vitest

• Mature .NET Framework application

• ASP.NET MVC

• SQL Server

• .NET MAUI mobile application for iOS and Android

• Public API

• Extensive payroll, banking, and benefits integrations

• Hosted on AWS

• Deployed with Azure DevOps

SPARK and AGL include AI-powered features such as document extraction and an AI assistant. As a result, some testing involves outputs that do not have a single “correct” answer and require evaluating quality and accuracy rather than exact matches.

• 5+ years of experience in software QA, including at least 2 years building or owning an automated test suite from the ground up

• Experience writing test automation in code for both browser and API testing using Playwright, Cypress, or similar tools

• Hands-on experience with continuous integration and deployment (CI/CD) pipelines such as GitHub Actions or Azure DevOps, with the ability to integrate testing into an existing deployment pipeline

• Proficiency in SQL sufficient to verify the underlying data behind a test

• Load and performance testing experience using JMeter, k6, Gatling, or similar tools, including experience designing a load-test plan without an existing template

• Experience writing or owning a rollback or incident runbook and the ability to discuss how it was used in practice

• Experience working alongside engineers as a peer within a two-week sprint cycle

• Working knowledge of security testing, including common injection and authentication vulnerabilities and the OWASP Top 10

• Current experience using AI tools as part of testing work, with a clear understanding of where they add value and where human judgment is still required

• Experience writing test code in TypeScript or JavaScript, the languages most of our automation will use

• Experience with .NET and C#, or experience building test coverage for a mature application with limited existing coverage

• Mobile application testing experience across iOS and Android

• Experience testing AI-powered features where outputs vary and testing focuses on accuracy or quality rather than exact matches

• Working knowledge of AWS, including the ability to read logs and set up a test environment

• Background in payroll, retirement plans, financial services, or another environment involving regulated or sensitive data

• Experience in a product organization that ships every one to two weeks or where multiple products share infrastructure

• Experience establishing quality reporting for leadership, including metrics such as escaped defects, time to fix, and hotfix rate