Quality Assurance Engineer

DiversyFund is hiring a Quality Assurance Engineer (QAE) to make sure our AI products do exactly what they should, every time. You'll test the AI email, text and calling campaigns we're building, the Halcrya platform, and the data underneath all of it. You'll work directly with our VP of Engineering and AI Product Development and our CTO/Chief Architect.

AI agents write much of our code and run much of our outreach. That makes a skeptical, technical tester more important, not less. You'll be the person who proves a release is ready, catches the agent that's confidently wrong, and makes sure no message goes to an investor or prospect that shouldn't.

You'll get hands-on mentoring, real ownership from week one, and a clear path to grow.

Term

Detail

Type

13-week contract, with the opportunity to extend or convert to full time

Rate

$30 to $40 an hour, based on experience

Hours

Full time, 40 hours a week

Start

As soon as possible

Location

San Diego, CA, on-site

Work authorization

Must be authorized to work in the US. We do not sponsor H-1B or other work visas, now or in the future.

Reports to

VP of Engineering and AI Product Development

• Test AI campaigns end to end. Write test plans and automated tests for AI email, SMS and calling campaigns: audience selection, personalization accuracy, scheduling, approval gates, sending, replies, and call flows and disclosures.
• Guard compliance in every send. Verify consent, opt-outs, quiet hours, suppression lists and rate limits work every time, so no message or call goes to someone who shouldn't receive it.
• Evaluate AI agents. Build golden datasets and evals for each agent, run them against every prompt or model change, and test for wrong answers, unsafe actions, prompt injection and data leaks.
• Check what agents test. Review agent-written tests to confirm they check the business requirement, not just what the code happens to do.
• Automate deterministic tests. Build end-to-end, API and integration tests for Halcrya and our investor and staff apps, and wire them into CI so a failing test blocks the release.
• Test data quality. Validate pipelines, migrations and imports; reconcile records across databases; catch duplicates, missing fields and bad joins before they reach campaigns, reports or investors.
• Test integrations. Cover email, SMS and voice providers, payment and KYC flows, webhooks and event delivery, including retries and failure cases.
• Own release readiness. Run regression and post-deploy smoke tests, check production monitoring after each release, and hand our Technology Operations team the evidence they need to accept it.
• Manage test data. Build synthetic and masked datasets so testing never needs real investor data.
• Report clearly. File precise, reproducible bugs and track quality metrics the whole team can see.

• 3 or more years as a QA engineer, QAE or SDET on web applications or APIs.
• Test automation in code: Playwright, Cypress or similar, in TypeScript (our main language) or Python.
• API and integration testing: REST APIs, webhooks, background jobs and third-party services, including failure and retry cases.
• Deterministic test design: stable, repeatable tests with controlled data and no flakiness, plus clear test plans and risk-based coverage.
• AI and agentic systems: hands-on experience testing LLM features or agents, including building evals, golden datasets or output checks.
• SQL: comfortable querying PostgreSQL to set up test data and verify results.
• CI/CD: tests running in pipelines such as GitHub Actions, with gates that block bad releases.
• AI-assisted development: you use tools like Claude Code or Cursor daily, and you catch their mistakes.
• Bug reporting: precise, reproducible defect reports, and you follow them through to the fix.
• Mindset: skeptical, detail-oriented and calm about saying "not ready to ship."
• Authorized to work in the US without sponsorship, and able to work on-site in San Diego.

• Fintech: payments, ACH, KYC, investor platforms, or work under SEC or FINRA rules.
• Testing email, SMS or voice systems such as SendGrid, Amazon SES or Telnyx.
• Marketing compliance: TCPA consent, CAN-SPAM, 10DLC.
• Eval tools such as promptfoo, Braintrust or LangSmith.
• Data quality testing: pipeline validation, reconciliation, Great Expectations or dbt tests.
• Security testing basics: OWASP Top 10, authorization checks, prompt injection.
• SOC 2 audit evidence or release-governance work.
• Next.js, Vercel or serverless apps.

We aim to go from first conversation to offer very quickly.

1. 20-minute screen with the VP of Engineering.
2. Interview/assessment on a small sample app with synthetic data. You'll write deterministic tests for a campaign flow, build an eval that catches an AI agent's bad outputs, and find the defects we've planted in its data and opt-out handling. AI tools are allowed; we grade judgment, not typing.
3. Review conversation walking through your assessment and past projects.
4. References, then an offer.

• If you love finding what's broken before anyone else does, apply immediately.