Sr Quality Assurance Engineer

Senior Quality Assurance Engineer

At Eleven, we thrive on solving complex challenges and pushing boundaries. We work at a rapid pace, embracing change, and staying laser-focused on delivering exceptional value to our customers. We're looking for visionary problem-solvers who excel in dynamic environments, embrace AI tools in streamlining work processes, adapt quickly, and drive innovation. If you love thinking outside the box, collaborating with top-tier talent, and having fun while making an impact—let's talk!

We are seeking a highly skilled and analytical Senior Quality Assurance Engineer to lead the quality assurance efforts for our core software applications. You will design, build, and execute robust automated and manual testing strategies that validate end-to-end functionality, high-throughput network authentication, API integrations, and data pipeline integrity. An ideal candidate is not a traditional black-box tester; you are a technical gatekeeper who understands underlying infrastructures, can query complex relational databases, and is comfortable leveraging AI tools to accelerate test coverage.

This role will report to the CTO and has no direct reports.

Essential job functions include:

• Automation framework design: Design, implement, and maintain advanced test automation frameworks for backend systems, network integrations, and multi-layered web applications.
• API validation: Lead end-to-end testing of RESTful APIs, third-party API integrations, and secure network communication workflows.
• Cloud infrastructure verification: Ensure cloud architectures deployed on AWS run flawlessly by testing deployments utilizing EC2, Lambda serverless environments, S3 storage, and DynamoDB tables. Ensure strict adherence to AWS IAM policies and security groups.
• Data & analytics testing: Formulate and execute rigorous T-SQL scripts to validate relational database schemas and data mutations. Manage and test search/indexing layers built on OpenSearch.
• Modern tooling integration: Incorporate and scale generative AI technologies into the testing workflow to auto-generate mock data, synthesize edge-case scenarios, and optimize boilerplate test script writing.
• Defect lifecycle leadership: Identify, document, isolate, and track bugs through Jira/Azure DevOps, providing deep technical insights (logs, network traces, stack traces) to accelerate developer remediation.

This role routinely uses standard office equipment such as computers, phones, and printers. This job operates remotely, in a home office environment. Travel requirements are minimal for this role.

While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to finger, handle, or feel objects, tools, or controls; reach with hands and arms; climb stairs; talk or hear. The employee must occasionally lift or move office products and supplies, up to 20 pounds. The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.

Must have:

• Experience: 8 years of professional software QA engineering experience, with a heavy emphasis on test automation and backend validation.
• Programming skills: Strong proficiency in C# and the.NET ecosystem, alongside experience writing, testing, and debugging PHP backend code.
• AWS cloud proficiency: Hands-on experience testing workloads deployed on core AWS architecture, specifically EC2 instances, AWS Lambda functions, S3, DynamoDB, and managing security parameters through AWS IAM.
• Databases & search engines: High proficiency with relational database systems using T-SQL (writing queries, stored procedures, joins) and validating telemetry or index structures inside OpenSearch/Elasticsearch.
• API testing expertise: Advanced mastery of RESTful API contracts, using tools like Postman, SoapUI, or automated clients.

Strongly preferred:

• AI-powered test automation: Hands-on experience with AI-assisted testing tools and frameworks (e.g., Playwright with AI-driven locators/self-healing selectors, Xray for intelligent test management and traceability) to reduce test maintenance overhead and flaky test rates.
• LLM-assisted QA workflows: Experience using LLMs (Claude, ChatGPT, etc.) for test case generation, log analysis, root-cause triage, or synthetic test data creation.
• AI tooling adoption: Active experience utilizing advanced AI technologies (e.g., GitHub Copilot, Claude API integrations) to speed up test execution or build intelligent mock services.
• CI/CD expertise: Proven track record of baking automated suites directly into continuous integration and deployment pipelines.
• Bachelor's degree in related field