Phantom is the modern money app used by tens of millions around the world. Our product combines everything people need to manage, spend, and grow their money in one simple, intuitive experience. Phantom brings all the control and flexibility of crypto-powered finance, without unnecessary complexity, into mainstream consumer finance.

By combining industry-leading security with thoughtfully designed tools, Phantom makes powerful financial tools feel approachable and easy to use. This focus on speed, control, and user experience has fueled rapid growth, with a community of 20M+ people, reaching #1 in the Google Play Store finance category, and consistently ranking as a Top 50 app across all categories, alongside some of the most recognizable consumer technology platforms in the world.

The Role

We're looking for an SDET for a 6 month contractor position who thinks like an engineer and tests like one too. You won't be writing test cases in a spreadsheet. You'll be designing and owning test infrastructure for financial-grade systems — payment flows, KYC pipelines, card transaction handling, and the compliance rails that underpin them.

This is not a QA role. It's an engineering role that happens to own quality as its primary output surface. You will work embedded in a team that ships production financial software at startup velocity. That means your job is to make speed and correctness coexist — not to be the brake pedal.

What You'll Own

Core Ownership

• Own test coverage for their squad's features end-to-end (unit, integration, E2E)

• Build and maintain automated test suites for new and existing functionality

• Run manual and exploratory testing on features before release

Automation & Infrastructure

• Write reliable, maintainable automated tests (UI, API, regression)

• Contribute to the shared test automation framework

• Integrate tests into CI/CD pipelines and ensure they run reliably on every PR/deploy

Quality Process

• Define and document QA standards within their squad

• Review PRs for testability and test coverage gaps

• Flag flaky tests and own resolution

Collaboration

• Partner with product engineers to shift testing left (writing tests alongside features, not after)

• Work with PM/design to clarify acceptance criteria before dev begins

• Surface quality risks and blockers early in the sprint

Qualifications

Core engineering:

• Strong proficiency in at least one of: Python, TypeScript/JavaScript, Go

• Experience designing and building test frameworks from scratch (not just adding tests to an existing suite)

• Deep familiarity with API testing — REST, webhooks, idempotency, retry behavior, edge cases at integration boundaries

• Working knowledge of databases (SQL) and the ability to write test data seeding/cleanup logic correctly

Financial systems (strong preference, will train for the right engineer):

• Experience testing payment flows, ledger systems, or compliance pipelines

• Understanding of idempotency, double-spend prevention, and eventual consistency in distributed systems

• Familiarity with webhook-based event systems and out-of-order delivery scenarios

CI/CD and infrastructure:

• Experience integrating test suites into CI pipelines (GitHub Actions, GitLab CI, or similar)

• Ability to instrument tests for flakiness detection, coverage tracking, and runtime performance

• Comfort operating in a cloud environment (AWS, GCP) and reading service logs/traces

Operational mindset:

• You can define what "this test passing" actually means in production terms

• You've contributed to or owned an incident post-mortem with concrete prevention steps

• You understand canary deployments, feature flags, and how to write tests that survive staged rollouts

What You'll Work On (Day 1 Context)

Your first 90 days will likely include:

• 30 days: map current test coverage against known failure modes; identify the top 3 gaps; ship at least one meaningful test suite that catches a real class of bugs

• 60 days: own CI quality gates for at least one pod's test suite; establish baseline metrics (coverage %, flakiness rate, regression