Build the test-data, mocking, and load-testing platforms that let Affirm engineers ship with confidence at scale

This role sits on Affirm's Test Enablers team within Developer Productivity, building platform capabilities for synthetic identities, test data seeding, mocking, deterministic testing, and load testing in support of a stated goal of scaling to 1,000 PRs/day by December 2027. It's a backend platform-engineering role (Python/Kotlin/Java) focused on shifting testing away from expensive E2E-only validation toward stronger component/integration/contract/performance testing, plus preparing infra for AI-assisted development workflows. Expect deep dives on distributed systems design, operational ownership (SLOs, runbooks, on-call), and driving ambiguous technical initiatives end to end.

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What this interview tests

Building and operating platforms for synthetic test data, mocking, and load testing
Shifting a test strategy from E2E-heavy toward component/integration/contract testing
Operational ownership: SLOs, alerting, runbooks, incident readiness for internal platforms
Diagnosing and fixing flaky or false CI failures at the systemic level
Leading ambiguous, medium-to-large technical projects end to end
Designing deterministic, observable validation feedback for AI-agent-driven development workflows

Common question themes

Describe a test/developer-productivity platform you built end to end, including test data or synthetic identity design

How have you shifted a team from E2E-heavy testing toward a stronger testing pyramid

Walk through how you added SLOs, alerting, and runbooks to a system you owned, and an incident that tested it

Tell me about diagnosing and eliminating flaky or false-failure CI signals

How would you design test validation feedback for an AI agent consuming CI signals, versus a human

Describe a time you led a technical project through high ambiguity with unclear requirements

How candidates describe it

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