puzzle.io - Senior Software Engineer, Quality Platform

Remote - U.S. or Canada$12k - $12k1mo ago

Remote Senior NA Fintech Artificial Intelligence Senior Software Engineer Automation Engineer REST GraphQL Selenium Cypress Playwright

Requirements

• We are looking for a senior engineer to help evolve how we validate product quality across our engineering organization. • This role might traditionally be called QA Automation Engineer, SDET, or Quality Engineer, but it is broader than those labels. We are not looking for someone whose primary job is to click through test plans or act as a release gate. We are looking for an engineer who can build systems, frameworks, workflows, and feedback loops that make our product safer and easier to change. • Our engineering team already owns quality as part of the development process. Engineers write unit tests, integration tests, and end-to-end tests, and we continue to invest in tooling that helps us validate features earlier and more confidently. • As our product surface area grows, we want to strengthen that foundation across our modern UI, GraphQL API, and partner-facing REST API. This role will help us build more complete, reliable, and scalable validation across those layers. • 7+ years of professional experience in software engineering, quality engineering, SDET, infrastructure, reliability, or a closely related technical role. • Strong software engineering fundamentals and the ability to write production-quality code, not just test scripts. • Experience designing and maintaining automated test frameworks for complex SaaS applications. • Hands-on experience with modern browser automation tools such as Playwright, Cypress, or Selenium. • Strong API testing experience, ideally with GraphQL and REST. • Experience testing complex business workflows involving state, permissions, data integrity, async jobs, integrations, and third-party systems. • Comfort working in CI/CD environments and understanding how tests should behave in pull requests, staging, release pipelines, and production-like environments. • Pragmatism about testing strategy. You know every bug does not require an end-to-end test, and every test does not belong in the UI. • Curiosity about AI-assisted engineering and testing, balanced with strong engineering judgment. • Clear communication around risk, tradeoffs, gaps, and why a certain kind of validation matters. • Experience in fintech, accounting, payroll, billing, tax, ERP, financial reporting, or other correctness-sensitive domains. • Experience testing multi-tenant SaaS applications. • Experience with schema-driven testing, contract testing, property-based testing, generated test cases, or model-based testing. • Experience with observability, synthetic checks, production validation, or SRE-style reliability practices. • Experience testing authorization, roles/permissions, audit trails, financial calculations, ledgers, reconciliation flows, or data pipelines. • Experience using LLMs or AI coding agents to generate tests, analyze failures, improve developer workflows, or build internal quality tools. • Experience with partner APIs, public APIs, SDKs, or integration ecosystems. • WHAT MAKES THIS ROLE DIFFERENT • This role is engineering-led. You will write code, reason about architecture, and influence how product engineers build and validate software. • This role is not limited to manual testing, although exploratory testing may be useful when it helps us understand risk or close a gap. • This role is not about adding end-to-end tests for everything. It is about building the right validation at the right layer. • This role is not about using AI for its own sake. It is about applying the right tools — AI, automation, deterministic checks, scripts, frameworks, or process changes — to improve quality in practical, measurable ways.

Responsibilities

• “How do we know this feature works?” • “How do we know existing workflows continue to work as the product evolves?” • “How do we validate API behavior before it impacts users or partners?” • “How do we make end-to-end tests high-signal, maintainable, and worth the cost?” • “How do we use AI thoughtfully without replacing good engineering judgment?” • You should be excited by testing, but your identity should be closer to software engineer who cares deeply about correctness, reliability, and product confidence than traditional QA. • Help define and build our quality engineering strategy across UI, API, data, and partner-facing surfaces. • Improve and extend end-to-end test coverage for high-value workflows, with an emphasis on maintainability, signal quality, and developer confidence. • Build deeper API-level validation for our GraphQL server and partner-facing REST surfaces, including contract testing, schema validation, regression coverage, and test data strategy. • Work with product engineers to choose the right level of validation for each problem: unit, integration, API, contract, end-to-end, synthetic monitoring, observability, or exploratory testing when appropriate. • Use AI and LLM-based tools thoughtfully to accelerate quality work, such as generating test cases, identifying coverage gaps, creating fixtures, analyzing failures, or building internal testing utilities. • Know when not to use AI. A script, deterministic check, schema validator, or focused test runner is often the better answer. • Help define what “done” means for features from a quality perspective, without becoming a bottleneck. • Mentor engineers on writing testable software, designing stable interfaces, and creating systems that are easier to validate. • Collaborate with engineering, product, customer success, and support to turn real customer workflows and production learnings into better automated coverage. • WHAT SUCCESS LOOKS LIKE • Our most important product workflows have clear, reliable validation. • Our end-to-end tests are focused, maintainable, and high-signal. • Our GraphQL and REST APIs have strong automated coverage around contracts, permissions, edge cases, partner-impacting behavior, and regression-prone areas. • Engineers trust feedback from the test suite and can act on failures quickly. • Release confidence improves without slowing the team down. • AI becomes a useful accelerator in the quality workflow, not a replacement for engineering judgment.

Benefits

• 100% paid employee health, dental, and vision plans • 10 observed holidays and a flexible PTO policy so you can recharge • $1000 home office budget to get you set up for success • $2400 co-working budget for face time with your colleagues • $600 learning and development budget • 401K so you can save for your future • And much more • Visa Sponsorship Notice: Puzzle does not provide visa sponsorship for new hires at this time. We can only consider candidates who are legally authorized to work in the U.S. or Canada without requiring new visa sponsorship or transfer of an existing visa. • Candidates should be currently residing in the U.S. or Canada to be eligible for this position. If hired, you will be required to present proof of work authorization. This employer is a participant of the E-Verify program.