Automation Test Lead/Architect

Maveric Systems Limited; Denver (CO); On-site; USD 90,000 - 130,000; Full time

Job summary

Maveric Systems Limited is seeking a quality engineering professional to advance automated testing across REST/SOAP, JSON/XML data validation, and AI-assisted testing workflows. The role emphasizes light scripting, code reading, and framework development rather than a pure application developer position.

The successful candidate will expand automated test coverage, drive efficient data conditioning, and integrate tests into CI/CD pipelines, leveraging Kiro and similar AI tools to accelerate

Qualifications

• Experience with test strategy, planning, regression and end-to-end testing, with defect management and quality reporting.

Responsibilities

• Increase automated test coverage, reduce manual testing effort.
• Integrate automated tests into CI/CD pipelines where appropriate.
• Assist with deployment readiness, smoke testing, regression testing, and production validation planning.
• Reverse engineer existing test assets and calculation validation approaches for modernization.
• Design and implement automated regression testing for annuity illustration calculations.
• Improve test case generation, execution, comparison, reporting and traceability.
• Use AI tools to generate test cases, analyze logic, create documentation, and accelerate modernization.
• Establish reusable testing patterns, validation frameworks, prompts, and AI-assisted quality engineering assets.

Skills

Test strategy

Test planning

Regression testing

Integration testing

End-to-end testing

Defect management

Test metrics

Traceability

Quality reporting

Data-driven testing

CI/CD

REST APIs

SOAP services

JSON

XML

Swagger/OpenAPI

Authentication flows

Request/response validation

Service-to-service testing

SQL Server

Kiro

Copilot

Amazon Q

Tools

CI/CD pipelines

SQL Server

Kiro

Copilot

Amazon Q

Job description

This role is primarily focused on quality engineering, test automation, API validation, regression testing, test data strategy, and AI-assisted testing. The resource should be comfortable reading code and performing light scripting, but this is not intended to be a traditional application developer role.

The successful candidate will help increase automated test coverage, reduce manual testing effort, improve quality and traceability, and use Kiro and other AI tools to accelerate end-to-end testing activities.

• Support REST API, SOAP/XML, JSON, integration, regression, and end-to-end testing.
• Validate service responses, transformation logic, request/response payloads, and downstream integrations.
• Support test data identification, data conditioning, and reusable test data strategies.
• Integrate automated tests into CI/CD pipelines where appropriate.
• Assist with deployment readiness, smoke testing, regression testing, and production validation planning.
• Reverse engineer existing test assets and calculation validation approaches to support modernization planning.
• Design and implement automated regression testing capabilities for annuity illustration calculations.
• Improve test case generation, execution, comparison, reporting, and traceability.
• Use Kiro and other AI tools to generate test cases, analyze existing logic, create documentation, and accelerate modernization activities.
• Help establish reusable testing patterns, validation frameworks, prompts, and AI-assisted quality engineering assets.

Skill Area

Needed Experience

Quality Engineering

• Test strategy, test planning, regression testing, integration testing, end-to-end testing, defect management, test metrics, traceability, and quality reporting.

Test Automation

• Framework design, automated regression suites, API automation, reusable test utilities, data-driven testing, automated comparisons, and CI/CD test execution.

API and Service Testing

• REST APIs, SOAP services, JSON, XML, Swagger/OpenAPI, authentication flows, request/response validation, and service-to-service integration testing.

Data and Validation Testing

• SQL Server query skills, database validation, test data creation, expected-result comparison, and data quality checks.

AI-Assisted Testing

• Hands-on use of Kiro, Copilot, Amazon Q, or similar tools for test generation, code analysis, documentation, impact analysis, and quality engineering workflows.

Technical Troubleshooting

• Ability to read application code, logs, pipeline outputs, API responses, and error messages to isolate issues and support root cause analysis.

Communication

• Ability to collaborate with QA, developers, business analysts, architects, actuarial teams, product owners, and vendor resources.