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Ai Automation Testing Jobs in Ohio (NOW HIRING)

As an Automation Test Lead, you will be instrumental in developing frameworks for automated testing ... Drive the adoption and effective use of AI and GenAI tools to improve testing efficiency ...

Establish and promote standards for dashboard development, documentation, testing, governance, and ongoing maintenance. * Identify business processes and workflows where AI, automation, or emerging ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A ...

Showing results 21-40

Ai Automation Testing information

What is AI automation testing?

AI automation testing refers to the use of artificial intelligence technologies to automate the process of testing software applications. This approach enhances traditional automated testing by using machine learning and data analysis to identify test cases, detect defects, and optimize test coverage. AI-driven testing tools can adapt to changes in the application, reduce manual effort, and improve the accuracy and speed of testing processes. As a result, organizations can deliver higher-quality software more efficiently.

What are the key skills and qualifications needed to thrive as an AI automation testing professional?

To thrive as an AI Automation Testing professional, you need a solid understanding of software testing principles, programming languages (such as Python or Java), and AI/ML concepts, often supported by a degree in computer science or a related field. Familiarity with automation tools like Selenium, Appium, and AI-powered testing frameworks, as well as certifications like ISTQB, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in diagnosing issues and collaborating with development teams. These skills ensure the delivery of robust, efficient, and reliable AI-driven software products in a competitive technology landscape.

What are some common challenges faced by AI automation testing professionals when validating machine learning models?

AI Automation Testing professionals often encounter challenges such as ensuring that test cases comprehensively cover the unique behaviors of machine learning models, dealing with non-deterministic outputs, and handling large datasets efficiently. It's also common to face difficulties in setting up reliable test environments that simulate real-world data scenarios. Collaboration with data scientists and developers is crucial to define meaningful metrics and effectively interpret test results, ensuring the AI system meets both functional and ethical standards.

What is the difference between Ai Automation Testing vs Software Test Engineer?

AspectAi Automation TestingSoftware Test Engineer
Required CredentialsCertifications in AI, automation tools, programming languagesSoftware testing certifications (ISTQB, CSTE), programming skills
Work EnvironmentFocus on automation frameworks, AI integration, scriptingManual and automated testing, test case design, bug tracking
Employer & Industry UsageTech companies, AI-driven projects, software development firmsSoftware development companies, IT departments, QA teams

Ai Automation Testing and Software Test Engineer roles overlap in testing skills and programming knowledge. However, Ai Automation Testing emphasizes AI integration and automation frameworks, while Software Test Engineers focus more on manual testing, test case creation, and bug identification. Both roles are essential in software quality assurance but serve different aspects of the testing process.

How to become an AI automation tester?

To become an AI automation tester, you should have a strong understanding of software testing principles, programming languages such as Python or Java, and experience with automation tools like Selenium or TestComplete. Familiarity with AI and machine learning concepts can be beneficial, along with certifications in testing or automation. Gaining hands-on experience through internships or projects is also valuable for this role.

Is AI automation testing a good career?

AI automation testing is a growing field within software quality assurance that involves using AI tools and scripting to automate test cases, increasing efficiency and coverage. It requires knowledge of programming, testing frameworks, and AI concepts, making it a valuable skill set with strong job prospects and competitive salaries.

What are popular job titles related to Ai Automation Testing jobs in Ohio?

For Ai Automation Testing jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Ai Automation Testing jobs in Ohio look for?

The top searched job categories for Ai Automation Testing jobs in Ohio are:

What cities in Ohio are hiring for Ai Automation Testing jobs?

Cities in Ohio with the most Ai Automation Testing job openings:

Infographic showing various Ai Automation Testing job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Software Developer / AI Engineer

PARKWOOD TRUST CO

Cleveland, OH โ€ข On-site

$120 - $160/hr

Other

Posted 3 days ago

New


Job description

The role of the Information Technology function is to develop, implement, and manage secure technology solutions that advance Parkwoodโ€™s goals and objectives. The Software Developer / AI Engineer will lead the design, development, implementation, and support of AI-enabled applications, intelligent agents, workflow automation, and data solutions. Working closely with business and technology partners, this employee will translate high-value use cases into responsible, scalable solutions that improve decision-making, streamline workflows, enhance access to information, and complement Parkwoodโ€™s internally developed and thirdโ€‘party systems.

Responsibilities

The responsibilities of the position include:

  • Partner with business leaders and colleagues to identify, prioritize, and define AI use cases aligned with Parkwoodโ€™s strategy, risk standards, and measurable business outcomes
  • Contribute to the continued development and execution of Parkwoodโ€™s AI strategy, roadmap, governance practices, and adoption approach
  • Design, build, test, deploy, and support secure AI applications and agents using Microsoft 365 Copilot, Copilot Studio, Azure OpenAI, Microsoft Foundry, and related Microsoft technologies
  • Develop enterprise AI solutions that utilize organizational documents, databases, Microsoft 365 content, and external APIs to deliver accurate, permissionโ€‘aware responses and automated actions
  • Implement retrievalโ€‘augmented generation, prompt and context management, agent orchestration, structured workflows, and humanโ€‘inโ€‘theโ€‘loop controls for complex business processes
  • Establish evaluation methods and monitoring for AI solutions, including response relevance, groundedness, accuracy, reliability, performance, cost, security, and user adoption
  • Apply responsible AI, privacy, accessโ€‘control, auditability, and dataโ€‘governance requirements throughout the solution lifecycle, particularly for sensitive financial and familyโ€‘office information
  • Integrate AI capabilities into internal web applications and business processes using C#/.NET, Blazor, Microsoft Graph, REST APIs, Power Automate, and approved data services
  • Build and maintain data ingestion, document processing, ETL, and API integrations that prepare trusted information for AI, reporting, and automation solutions
  • Create reusable technical patterns, documentation, testing standards, and deployment practices that support scalable and maintainable AI development
  • Collaborate with crossโ€‘functional teams, educate users on effective and responsible AI practices, gather feedback, and continuously improve solutions
  • Continue to develop and support traditional applications, financial and investment reports, and business intelligence solutions where they enable or complement AIโ€‘driven workflows
Background and Work Experience
  • Bachelorโ€™s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field, or equivalent practical experience
  • 5+ years of professional experience in software development, including meaningful handsโ€‘on experience delivering AI, automation, data, or intelligent application solutions
  • Demonstrated ability to move AI solutions from business discovery and prototyping through testing, deployment, monitoring, and ongoing support
  • Strong proficiency in:
  • Microsoft 365 Copilot extensibility, Copilot Studio, and agent development
  • Azure OpenAI and Microsoft Foundry, including prompt design, model selection, evaluation, deployment, and monitoring
  • Retrievalโ€‘augmented generation, semantic and hybrid search, vector embeddings, document chunking, and grounding enterprise content
  • C# and .NET, including web application development with Blazor and integration of AI services through APIs and SDKs
  • Python for AI prototyping, data transformation, scripting, or service integration
  • Microsoft SQL Server, Azure SQL Database, data modeling, and secure dataโ€‘access patterns
  • Microsoft Graph, REST APIs, OAuth, managed identities, roleโ€‘based access controls, and secure integration practices
  • Azure DevOps, source control, automated testing, CI/CD, application lifecycle management, and production support
  • Microsoft Power Platform, including Power Automate and Power BI
Other Desirable Attributes Jack, Joseph and Morton Mandel Foundation All content submitted to or received from this website is secure as to protect the information of the individuals.
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