Senior SDET

Lead with quality judgment: Challenge requirements and assumptions; distinguish verification (does it work as specified?) from validation (does it solve the user problem?); identify failure modes, edge cases, and business risks beyond happy paths.

Test from the customer’s perspective: Map real user workflows, anticipate misuse and operational edge cases, and assess real-world impact; partner early with Product and Engineering to refine acceptance criteria and prevent defects.

Design risk-based test strategy: Select the right mix of unit, API, contract, integration, UI, end-to-end, exploratory, regression, and non-functional testing based on product risk, feedback speed, confidence needs, and maintenance cost.

Build durable quality engineering systems: Create reusable tooling, libraries, test-data capabilities, environment utilities, CI integrations, and diagnostic/observability patterns that improve quality for the team and can be adopted by adjacent teams.

Perform hands-on product investigation: Conduct functional and exploratory testing of complex workflows, integrations, and edge cases when it provides the fastest or highest-confidence signal; translate discoveries into clear defects, risk assessments, and durable automated coverage where appropriate.

Lead quality-risk decisions: Identify, analyze, and prioritize product risks; derive test conditions and appropriate coverage depth; communicate residual risk and help the team decide what “good enough” means for each release.

7-10 years of progressive experience in software engineering, SDET, quality engineering, developer productivity, or test-platform engineering, including 5+ years building and evolving automation or test infrastructure.

Evidence of owning an automation framework, test platform, internal developer tool, CI quality gate, or engineering system from architecture through adoption, operational support, and iterative improvement.

Experience testing modern systems beyond a single web UI: APIs, asynchronous workflows, distributed services, event-driven systems, data flows, third-party integrations, authentication/authorization, and failure recovery.

Strong hands-on experience with Playwright and TypeScript preferred, with the ability to explain trade-offs among UI, API, contract, component, integration, end-to-end, performance, resilience, and exploratory testing.

Experience making automated testing trustworthy at scale: parallelization, isolation, deterministic test data, environment provisioning, observability, flaky-test diagnosis, retry policy design, quarantine/remediation workflows, and actionable reporting.

Strong CI/CD experience, including test selection or test-tiering strategies, PR quality gates, artifact collection, failure triage, and reducing feedback time without weakening coverage.

Ability to design and validate APIs and service boundaries using techniques such as schema validation, consumer/provider contract testing, mocks/stubs/fakes, service virtualization, and backward-compatibility testing.

Clearly articulates and applies the difference between verification and validation, with examples of when each shaped their test approach and delivery decisions.

Proven ability to analyze requirements and designs to uncover gaps, ambiguous behavior, and high-risk areas before implementation, using reviews, checklists, and structured quality risk analysis.

Demonstrated skill in designing tests around real user journeys, business workflows, and failure scenarios rather than just API endpoints or UI components in isolation.

Experience using risk-based testing to prioritize which areas to test, at what depth, and with which techniques when time and resources are constrained.

Habitually challenges assumptions from developers, PMs, and stakeholders in a collaborative way that improves the product and reduces downstream defects.

Ensures test failures produce useful evidence—logs, network traces, screenshots/video where relevant, and clear failure classification.

Hands-on experience using AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot, or equivalent to accelerate coding, refactoring, test design, failure analysis, documentation, and exploratory investigation.

Demonstrated ability to evaluate AI-generated test code for correctness, determinism, maintainability, meaningful assertions, security/privacy implications, and false confidence.