QA Lead- AI / Automation

REDLEO SOFTWARE INC.

United States

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) JavaScript (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Application Testing Automation of Tests Microsoft Azure Software Bug Management Cloud Foundry Code Coverage Software Quality

+32 more

Databases Continuous Integration DevOps JSON Python (Programming Language) Log Analysis Microsoft SQL Server Microsoft UI Automation MySQL Scrum Methodology Productivity Software E2e Testing Selenium Simple Object Access Protocol (SOAP) SQL Databases Software Testing Automation Framework Test Case Test Data Strategies of Testing User Interface Testing Web Services Extensible Markup Language (XML) Google Cloud Enterprise Software Applications Cloud Platform System GitHub Copilot SOAPAPI Generative AI Restful APIs Splunk Api Management Microservices

Requirements

Looking for a QA lead with 8+ years of experience in Quality Engineering, Test Automation, API/ UI testing CI/CD and AI-led testing, with strong technical leadership and the ability to defile and drive QA Strategy
Strong experience in software quality engineering, test strategy, test planning, and QA leadership across enterprise applications.
Ability to define and drive the overall Quality Engineering strategy, establish automation and quality standards, identify risks early, and continuously improve the organization’s testing maturity and release quality.
Strong hands-on experience in API testing and automation using REST/SOAP services.
Expertise in UI automation testing using Selenium or equivalent frameworks.
Experience designing and implementing test automation frameworks using Java, Python, JavaScript, or similar technologies.
Strong experience in functional, integration, regression, system, API, and end-to-end testing.
Experience integrating automated testing with continuous integration and continuous delivery (CI/CD) environments.
Strong knowledge of Agile/Scrum, Shift-Left Testing, Continuous Testing, and Quality Engineering practices.
Experience with SQL and database validation, including MySQL/SQL Server or equivalent databases.
Strong understanding of JSON, XML, REST APIs, SOAP, web services, and microservices architectures.
Strong experience with cloud environments, preferably Pivotal Cloud Foundry and/or AWS/Azure/Google Cloud Platform.
Knowledge of Splunk or equivalent production monitoring tools for log analysis, troubleshooting, and root-cause identification.
Experience establishing QA metrics, quality gates, defect management, test coverage, and release-readiness criteria.
Ability to lead test automation strategy and framework modernization, reducing manual testing and improving release velocity.
Strong experience in AI-led Quality Engineering, leveraging AI/GenAI capabilities to improve test planning, test design, automation, execution, defect analysis, and overall software quality.
Preferably generating test case and script creation using copilot.
Experience using AI-assisted test generation and automation tools to generate test scenarios, test cases, automation scripts, regression suites, and test data.
Experience leveraging AI/GenAI for defect analysis, root-cause analysis, log analysis, failure prediction, and intelligent test prioritization.
Experience evaluating and adopting AI-powered QA/testing tools to improve testing efficiency, coverage, productivity, and quality.
Hands-on experience with AI development/productivity tools such as GitHub Copilot or equivalent AI tools, with the ability to apply them effectively in QA automation and Quality Engineering activities.
Ability to identify opportunities where AI can replace or augment repetitive manual QA activities and drive measurable improvements in automation and productivity.
Understanding of AI/ML application testing, including validation of AI-driven functionality, data quality, model behavior, accuracy, reliability, and edge cases, where applicable.
Experience mentoring QA engineers and providing technical leadership across distributed and cross-functional teams.
Strong collaboration skills with Development, Product, Architecture, DevOps, and Business teams.
Excellent technical communication skills with the ability to communicate effectively with technical and non-technical stakeholders.
Strong analytical and problem-solving skills with the ability to identify root causes, assess impact, define action plans, and drive issues to closure.
Experience delivering quality solutions in financial/banking applications is preferred.
Strong attention to detail and ability to work effectively in a dynamic, fast-paced environment.