Test Automation Engineer - SDET

Test Automation Engineer - SDET Hybrid - Washington, DC Role Summary: We are seeking a hands-on Software Development Engineer in Test (SDET) to support election-critical systems through the November elections cycle. Working closely with the current Elections QA Lead, this person will help offload testing and automation work, with a particular emphasis on the distribution side of the platform. This is not a pure automation role. Beyond strong automation, API testing, AWS observability, and backend validation skills, the ideal candidate operates like a quality engineer who understands production risk — someone who can clarify requirements, challenge gaps, assess production impact, and help strengthen quality engineering (QE) processes. Practical, institutional knowledge of U.S. elections and the risks associated with election result distribution is essential. The successful candidate will be comfortable working in a fast-paced Agile environment, maintaining quality discipline under election-cycle pressure, and communicating testing progress, automation value, risks, and quality improvements to stakeholders. Key Responsibilities: Partner with the Elections QA Lead and take ownership of assigned distribution-side testing workstreams, independently handling automation, API validation, log analysis, and test coverage expansion. Design and maintain automated tests for UI and API layers using Playwright and TypeScript. Build and maintain API automation using Rest Assured, including request/response validation, status code and header checks, error handling, negative testing, contract testing, and data integrity validation. Perform XML and JSON schema validation and design test scenarios from API specification documentation. Analyze AWS CloudWatch logs to identify API usage patterns, failure trends, and coverage gaps, converting real production usage into meaningful automated test coverage. Validate backend data in MongoDB collections and support distribution-side quality across API, backend, data, and schema workflows. Apply risk-based testing to identify high-risk workflows and prioritize coverage based on business and production impact. Review requirements critically — testing beyond what is written in the ticket — and proactively clarify unclear requirements, missing acceptance criteria, and edge cases with stakeholders. Manage test cases, execution, defects, and traceability in Jira and Zephyr. Contribute to release readiness reviews, defect triage, and go/no-go decisions, and participate in blameless postmortems to convert findings into preventive actions. Communicate risks clearly and professionally, pushing back respectfully when process shortcuts create quality or production risk — without creating unnecessary noise or escalation. Demonstrate value to stakeholders by broadcasting automation improvements, risk reduction, coverage gains, and ROI, and bring a continuous-improvement mindset to strengthen the overall QE practice. Required Skills & Qualifications: Test Automation Strong hands-on experience with Playwright for UI and API automation. Strong coding and scripting experience with TypeScript. API Testing Hands-on API automation experience using Rest Assured. Strong experience testing REST APIs, including request/response validation, status code validation, header validation, error handling, negative testing, contract testing, and data integrity testing. Experience with XML and JSON schema validation. Ability to design test scenarios from API specification documentation. Experience writing BDD-style test scenarios and acceptance criteria. AWS Observability & Backend Validation Working knowledge of AWS for test validation and production behavior analysis. Ability to analyze CloudWatch logs to determine API usage patterns, failure trends, and missing test coverage, and to convert production usage patterns into automated coverage. Experience working with MongoDB collections for backend data validation. Process, Tools & Collaboration Hands-on experience with Jira and Zephyr for test case management, defect tracking, test execution, and traceability. Strong understanding of risk-based testing and the ability to prioritize coverage based on production and business impact. Experience working in a highly Agile environment with fast-moving delivery teams. Ability to push back professionally when the team deviates from agreed process, quality gates, or acceptance criteria. Strong stakeholder communication skills, with the ability to work with product owners, developers, QA leads, and business stakeholders to clarify requirements and acceptance criteria. Elections Domain Knowledge (Required) Institutional knowledge of U.S. elections is a must, including: Election results workflows and race-level data Vote updates, vote types, and race calls Result distribution and downstream consumer impact Election-night risk areas Preferred (Nice-to-Have) Skills Python scripting experience for test utilities, data validation, log analysis, or automation support. Experience with boto3 for AWS-based automation or validation. Experience with AI-led test automation tools or frameworks — using AI to support test scenario generation, automation script generation, regression impact analysis, and test coverage recommendations. Experience testing media, publishing, news, or real-time data distribution platforms. Experience supporting production-critical systems during high-visibility, time-sensitive events. Experience with release readiness reviews, defect triage, and go/no-go decisions. Experience with observability-driven testing, where production logs and usage data are used to improve test coverage. Experience participating in or facilitating blameless postmortems. Experience communicating automation ROI and quality value to both technical and business stakeholders. Ideal Candidate Profile The ideal candidate is more than a test automation engineer — they operate like a quality engineer who understands production risk. They can: Take ownership of distribution-side testing workstreams and reduce the workload on the current QA Lead by working independently. Identify high-risk workflows and prioritize testing based on business and production impact. Use CloudWatch logs to understand real API usage and add tests where coverage gaps exist. Bring practical QE process improvements to reduce production misses. Communicate risks clearly without creating noise, and demonstrate value through measurable improvements in automation, risk reduction, coverage, and ROI. Work under election-cycle pressure without cutting corners on quality.