Software Development Engineer IV - QA

At Jumio, the Software Development Engineer IV - QA (SDE-IV, QA) is a senior technical role focused on ensuring the quality, performance, and reliability of highly scalable web portals and distributed backend systems. Our platform spans multiple Java Spring Boot microservices and customer-facing web portals, deployed across AWS ECS, EKS, and Lambda, and integrated through event-driven messaging using SNS/SQS.

In this role you will design and drive the test automation strategy for both UI (Playwright) and API/service layers, set the quality bar for the team, and act as a force multiplier — mentoring other engineers and embedding quality earlier in the development lifecycle. You will work closely with development, product, and DevOps teams to ensure our products meet the highest standards of quality, scalability, and security.

This is a hands-on senior IC role: you will write code, but you will also influence architecture, own cross-service test strategy, and make build-vs-buy decisions for testing tooling.

As part of Jumio's engineering culture, you will adopt a T-shaped engineering approach. Beyond deep expertise in test automation and quality engineering, you will contribute across the development lifecycle — understanding software architecture, participating in design and API-contract discussions, reviewing application code, and ensuring our distributed systems are testable, observable, and resilient by design.

This role is critical to ensuring the reliability, scalability, and security of Jumio's products. By architecting and maintaining automated testing frameworks across web, API, and event-driven layers, you will enable faster, higher-confidence releases and reduce production risk in a complex microservices environment.

Test Architecture & Strategy

• Define and own the end-to-end automated test strategy across web portals and backend microservices, balancing UI, API, contract, integration, and end-to-end coverage (test pyramid).
• Design test strategies for distributed, event-driven systems — including asynchronous flows through SNS/SQS, eventual consistency, idempotency, message ordering, retries, and dead-letter handling.

Automation Engineering

• Develop and maintain robust test automation frameworks for web (Playwright, Selenium, or equivalent) and API testing, using Java and/or JavaScript/TypeScript.
• Automate API and service-level testing (REST/JSON, and async messaging) to validate functionality, performance, and resilience.
• Build maintainable, scalable framework abstractions (page objects, fixtures, data builders, reusable test harnesses) that other engineers adopt.

Cloud-Native & Non-Functional Testing

• Design tests that run against services deployed on ECS, EKS, and Lambda, including environment provisioning and teardown.
• Use tools like TestContainers / LocalStack to test AWS integrations (SQS/SNS, Lambda, etc.) reliably and locally.
• Drive performance, load, and resilience testing (e.g., JMeter, k6, Gatling, Locust) for highly scalable services, and partner with engineering on results and bottlenecks.
• Contribute to non-functional quality: basic security testing, reliability, and chaos/failure-injection where appropriate.

CI/CD & Quality Engineering

• Integrate automated test suites into CI/CD pipelines (e.g., GitHub Actions / Jenkins / GitLab CI) to enable fast feedback and continuous delivery.
• Improve test reliability — reduce flakiness, optimize execution time, enable parallelization, and improve observability of test results.
• Define and track quality metrics (coverage, escape rate, MTTR, flake rate) and use them to drive decisions.

AI-Augmented Engineering

• Leverage LLM-based tools (e.g., GitHub Copilot, Claude Code, Cursor) to accelerate test authoring, framework development, test-data generation, and debugging — driving measurable productivity and coverage gains.
• Apply AI to quality engineering workflows: generating and maintaining test cases from requirements/specs, summarizing failures and triaging flaky tests, reviewing code, and scaffolding boilerplate so the team focuses on high-value testing.
• Champion responsible, effective AI adoption within the QA team — establishing prompts, patterns, and guardrails, and mentoring engineers on using these tools to work faster without compromising rigor or correctness.

Collaboration & Leadership

• Partner with developers to ensure comprehensive coverage and efficient issue resolution; review application and test code.
• Mentor and uplevel SDE-II/III QA engineers on automation best practices, framework design, and testing strategy.
• Influence design and architecture discussions to make systems more testable and to shift quality left.
• Continuously evaluate and introduce new tools, methodologies, and best practices.

• Strong programming skills in Java (Spring Boot ecosystem) and/or JavaScript/TypeScript.
• Deep, hands-on experience with Playwright (and/or Selenium) for web automation.
• Proven experience testing microservices and API-based systems, including async/event-driven architectures (SNS/SQS or equivalent messaging — Kafka/RabbitMQ a plus).
• Experience testing cloud-native applications on AWS (ECS, EKS, Lambda) and familiarity with containers/Docker and Kubernetes.
• Solid grasp of CI/CD, test integration, and pipeline quality gates.
• Experience with performance/load testing and non-functional quality.
• Experience with API automation tools (e.g., Postman, REST-assured) and a good understanding of REST APIs.
• Basic knowledge of UNIX/Linux systems and scripting.
• A problem-solving mindset, strong attention to detail, and the ability to drive quality decisions and mentor others in a fast-paced environment.
• Hands-on experience using LLM/AI coding assistants (GitHub Copilot, Claude Code, Cursor, or similar) to improve engineering productivity, with good judgment on where AI accelerates work and where human review is essential.

Nice to Have

• Contract testing (Pact, Spring Cloud Contract).
• Infrastructure-as-Code familiarity (Terraform/CloudFormation) and observability tooling (CloudWatch, Datadog, Grafana).
• Experience in identity verification, KYC/AML, or other security/compliance-sensitive domains.
• Experience building or testing LLM/AI-powered features, or integrating AI into test automation and CI/CD workflows.