Top Remote Senior Level QA & Test Engineering Jobs in Boston, MA

Perform functional and automated software testing, create test plans and cases, document bugs and quality risks, verify releases, collaborate with engineering and product teams, and mentor junior QA engineers. The role requires expertise in QA methodologies, API testing, SQL, Unix/Linux log analysis, test automation, and Java or mobile-language development within Agile SaaS environments.

Develop and implement test plans for coherent optical communication products, analyze transceiver performance, define testability requirements, validate platforms, support fault isolation, and improve manufacturing test yield and cycle times. The role requires collaboration with development and manufacturing teams, statistical modeling, SQL-based data analysis, and familiarity with optics and test technologies.

Lead development and implementation of automated test strategies, frameworks, and test environments for the eLxr Linux distribution. Design, integrate, and verify tests for safety-critical embedded and enterprise systems, mentor engineers, improve tooling and workflows, and collaborate with product and global engineering teams to deliver scalable, high-quality solutions.

Design, build, and maintain automated test frameworks and scripts. Lead test strategy, planning, and execution across functional, load, integration, security, server-side, and ETL testing. Create test artifacts, run automated tests, analyze results, report defects, participate in CI/CD, code reviews, and agile ceremonies, and drive issue resolution.

Design, develop, and execute automated tests, perform API and performance testing, identify and document defects, collaborate with cross-functional teams to ensure product quality and resolve issues.

Develop and maintain automated testing frameworks and suites for UI, API, integration, database, functional, regression, and end-to-end testing. Create test strategies, plans, cases, and scenarios; validate system controls and compliance requirements; manage defects; analyze quality metrics; and support release and production validation. Collaborate with product, business analysis, development, and DevOps teams throughout the software development lifecycle.

Senior QA Engineer responsible for designing and executing test strategies for Amazon Connect contact centers, building manual and automated Playwright/Cypress/Selenium suites across UI, API and serverless backends, validating migrations and production readiness, running UAT, incident triage, and mentoring junior QA engineers.

Develop and maintain AI-based ASIC verification automation flows, regression infrastructure, dashboards, reporting tools, and triage automation. Build scripts and integrations using Python, Perl, Tcl, shell scripting, and Make. Support simulation, coverage, lint, formal, emulation, continuous integration, EDA tool integration, and distributed compute infrastructure. Debug automation, tool, runtime, licensing, queue, and workflow issues while improving verification reliability, reproducibility, and efficiency across geographically distributed engineering teams.

Performs software integration, verification, validation, interoperability, regression, data migration, and exploratory testing for VA healthcare systems. Analyzes requirements, creates traceable test cases and plans, executes tests across distributed applications, validates databases and web services, manages defects, and prepares status, execution, and analysis reports. The role requires expertise in healthcare IT, SOA, SOAP/REST, FHIR, HL7, test management tools, and collaboration with technical teams and stakeholders.

Lead the strategy, architecture, and implementation of automated data testing frameworks for Databricks Lakehouse platforms. Validate Delta Lake tables, batch and streaming pipelines, data lineage, governance controls, performance, and scalability. Integrate quality tests into CI/CD workflows, establish engineering standards, and mentor data QA engineers. The role requires deep expertise in Python, PySpark, Spark SQL, Databricks, testing frameworks, and cloud infrastructure.