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Ai Automation Testing Jobs in Indiana (NOW HIRING)

Virtusa Corporation

Senior Consultant

Indianapolis, IN · On-site

... automation, decision-making, and user experience Collaborate with cross-functional teams to deliver end-to-end solutions and drive innovation Leverage AI tools to accelerate development, testing, and ...

Virtusa Corporation

Senior Consultant

Indianapolis, IN · On-site

... automation, decision-making, and user experience Collaborate with cross-functional teams to deliver end-to-end solutions and drive innovation Leverage AI tools to accelerate development, testing, and ...

Virtusa Corporation

Senior Consultant

Indianapolis, IN · On-site

... automation, decision-making, and user experience Collaborate with cross-functional teams to deliver end-to-end solutions and drive innovation Leverage AI tools to accelerate development, testing, and ...

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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.

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Ai Automation Testing jobs near you

.NET Full Stack Developer with AI (C#, Angular & LLM Integration) - Q3 - 2026

R2 Technologies Corporation

Indianapolis, IN • On-site

Full-time

Posted 23 days ago

Job description

Overview:
About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we provide IT staffing and digital product engineering services to clients ranging from startups to Fortune 1000 companies. In addition to talent services, R2 develops proprietary solutions including SmartEnt, an enterprise AI and IoT intelligence platform. We work closely with our clients to deliver technology outcomes that are realistic, measurable, and impactful.
Job Summary: The .NET estate inside most enterprises is where AI has to land to be useful, and the Microsoft stack now has a first-class path to get it there. R2 Technologies is seeking a .NET Full Stack Developer with AI experience to build and maintain enterprise applications that embed Generative AI capabilities. You will work across .NET Core services, Angular front ends, and SQL Server data layers, integrating LLM-powered features such as document search, retrieval-augmented generation, chatbots, and intelligent workflow automation using Azure OpenAI and Semantic Kernel.
Key Responsibilities:
  • Design, develop, and maintain full stack applications using .NET Core/.NET 8, C#, Angular, and SQL Server.
  • Integrate Generative AI capabilities into enterprise applications using Azure OpenAI, Semantic Kernel, or Python-based LangChain services.
  • Build AI-powered features including chatbots, document search, RAG workflows, and intelligent process automation.
  • Develop and consume RESTful APIs and microservices that connect Angular front ends to backend AI services.
  • Design and optimize database schemas, stored procedures, and data models in SQL Server, and implement vector search using Azure AI Search or comparable stores.
  • Implement security best practices, coding standards, unit testing, and CI/CD pipelines within Agile/Scrum delivery.

Qualifications:
  • 3 years of full stack development experience with hands-on Generative AI or LLM integration work.
  • Strong expertise in C#, .NET Core/ASP.NET Core, Angular (v12+), and SQL Server.
  • Experience integrating LLMs such as Azure OpenAI, OpenAI, or Anthropic Claude into enterprise applications.
  • Hands-on experience with Semantic Kernel, LangChain, or comparable AI orchestration frameworks.
  • Proven experience developing REST APIs and microservices, with a strong grasp of object-oriented design patterns.
  • Familiarity with vector databases such as Azure AI Search, Pinecone, or ChromaDB, and deployment on Azure Cloud.

Skills:
.NET Core,C#,Angular,SQL Server,Generative AI,Azure OpenAI,LLM Integration,REST APIs,Full Stack Development

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