Sr. Quality Assurance Engineer (REMOTE- US based only)

We are seeking a Sr. Quality Assurance Engineer (REMOTE) for a full time and direct hire role for one of our amazing partners in the United States. This role is remote, but you MUST be living in the United States and be a US Citizen or Green Card Holder. This role does NOT offer sponsorship, it's NOT a consulting role, and we do NOT work with 3rd parties! Overview: We're looking for a highly technical and analytical Senior Quality Assurance Engineer to take ownership of quality across core software applications. You will design, develop, and maintain automated testing frameworks across backend services, APIs, cloud infrastructure, network integrations, and web applications. You'll play a key role in validating high-volume authentication workflows, third-party integrations, data pipelines, and overall system performance. You will work closely with engineering and technology leadership to identify potential issues early, improve test coverage, reduce defects, and help ensure reliable software releases. You will be responsible for developing comprehensive automated and manual testing strategies that ensure reliable, scalable, and secure software. This role goes beyond traditional black-box testing. You'll need to understand the underlying application and cloud infrastructure, work comfortably with APIs and databases, troubleshoot complex issues, and use technical data to identify the root cause of defects. This is a fast-moving environment where adaptability, creative problem-solving, and a willingness to use emerging technologies, including AI, are encouraged. We're looking for someone who enjoys finding better ways to test, automate, troubleshoot, and improve software quality. We are looking for someone who is technically curious, highly analytical, and comfortable getting deep into the technology stack. Someone who naturally asks why something failed rather than simply documenting that it failed. You'll thrive in this position if you enjoy solving complex problems, working across application and infrastructure layers, building automation from the ground up, and continuously looking for ways to make QA more efficient through modern tools and AI. You will be a true technical partner to engineering, not simply a tester at the end of the development cycle. Responsibilities: Test Automation & Framework Development • Design, build, and maintain scalable automated testing frameworks. • Develop automated coverage for backend systems, APIs, network integrations, and complex web applications. • Create reliable, maintainable test suites that minimize flaky tests and improve release confidence. • Balance automated and manual testing based on application risk and requirements. API & Integration Testing • Lead end-to-end testing of RESTful APIs and third-party integrations. • Validate API contracts, authentication processes, data exchanges, and error handling. • Test secure communication workflows and integrations across multiple systems. • Use tools such as Postman, SoapUI, or automated HTTP clients to validate API functionality. Cloud & Infrastructure Testing • Test applications and services running within AWS environments. • Validate functionality across EC2, Lambda, S3, and DynamoDB. • Verify deployments, configurations, permissions, security groups, and IAM policies. • Identify infrastructure-related issues that could impact application functionality, reliability, or security. Database & Data Validation • Write and execute complex T-SQL queries to validate database structures and data changes. • Test stored procedures, joins, schemas, and data transformations. • Validate data pipelines and telemetry to ensure information is accurate and complete. • Test search and indexing functionality using OpenSearch or Elasticsearch. AI-Enhanced QA • Explore and implement AI-powered tools to improve testing efficiency and coverage. • Use generative AI to create mock and synthetic data, generate edge-case scenarios, and accelerate test development. • Leverage LLMs to assist with test case creation, log analysis, troubleshooting, and root-cause investigation. • Identify opportunities to incorporate AI into QA workflows while maintaining appropriate technical oversight and accuracy. Defect Management & Troubleshooting • Identify, reproduce, isolate, document, and track software defects. • Manage defects through tools such as Jira or Azure DevOps. • Provide developers with detailed technical information, including application logs, network traces, stack traces, and reproduction steps. • Partner with engineering teams to determine root causes and accelerate resolution. Requirements: • 8+ years of professional software QA engineering experience with a strong emphasis on automation and backend testing. • Strong experience developing and maintaining automated testing solutions. • Proficiency with C# and the .NET ecosystem. • Experience working with, testing, and debugging PHP backend applications. • Hands-on experience testing applications and workloads running in AWS. • Strong working knowledge of AWS EC2, Lambda, S3, DynamoDB, and IAM. • Advanced SQL and T-SQL skills, including queries, joins, stored procedures, and database validation. • Experience testing relational databases and complex data structures. • Experience working with OpenSearch or Elasticsearch, including search and indexing validation. • Strong understanding of RESTful APIs and API testing methodologies. • Experience using API testing tools such as Postman, SoapUI, or automated HTTP clients. • Strong analytical and troubleshooting skills with the ability to investigate issues beyond the user interface. Preferred Qualifications • Experience using AI-powered testing tools and frameworks, including technologies that support intelligent locators, self-healing selectors, or automated test maintenance. • Experience with tools such as Playwright and Xray. • Practical experience using ChatGPT, Claude, or similar LLMs for test generation, log analysis, root-cause analysis, and synthetic data creation. • Experience using GitHub Copilot, Claude APIs, or other AI development tools to improve QA workflows. • Experience building AI-assisted mock services or test environments. • Strong understanding of CI/CD practices and experience integrating automated testing into deployment pipelines. • Experience working in high-growth or rapidly evolving technology environments. • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. You must be legally authorized to work in the United States without current or future sponsorship.