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Ai Automation Testing Jobs in Indiana (NOW HIRING)

Provide technical leadership and direction for AI/ML and agent-based automation initiatives * Partner with engineering and QA teams to embed AI/ML solutions into development, testing, and CI/CD ...

$140K - $185K/yr

Own end-to-end implementation of AI solutions, from concept through production, including testing ... Hands-on experience integrating APIs and building automation workflows across multiple systems (e.g ...

$140K - $185K/yr

Own end-to-end implementation of AI solutions, from concept through production, including testing ... Hands-on experience integrating APIs and building automation workflows across multiple systems (e.g ...

$140K - $185K/yr

Own end-to-end implementation of AI solutions, from concept through production, including testing ... Hands-on experience integrating APIs and building automation workflows across multiple systems (e.g ...

Own end-to-end implementation of AI solutions, from concept through production, including testing ... Hands-on experience integrating APIs and building automation workflows across multiple systems (e.g ...

$140K - $185K/yr

Own end-to-end implementation of AI solutions, from concept through production, including testing ... Hands-on experience integrating APIs and building automation workflows across multiple systems (e.g ...

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Ai Automation Testing information

What are the key skills and qualifications needed to thrive as an AI Automation Testing professional, and why are they important?

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 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 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.

What are popular job titles related to Ai Automation Testing jobs in Indiana? For Ai Automation Testing jobs in Indiana, the most frequently searched job titles are:
What cities in Indiana are hiring for Ai Automation Testing jobs? Cities in Indiana with the most Ai Automation Testing job openings:

AI Engineer & Automation Lead

Prophecy Technologies

Indianapolis, IN • On-site

Full-time

Posted 26 days ago


Job description

Role Overview:
The AI Engineer & Automation Lead will design, implement, and operationalize automation and AI capabilities that enhance the efficiency, quality, and compliance of digital content operations within a highly regulated Life Sciences environment.
Key Responsibilities:
  • Build AI-driven solutions to improve speed, accuracy, and compliance across the content lifecycle.
  • Develop smart automation for automated QC for email, banner, PDF, and IVA assets.
  • Create and maintain an AI powered PDF/document comparison engine to accelerate regulatory review, ensuring alignment with source files, claim references, and approved content.
  • Design and implement AI-based PDF annotation capabilities, enabling automated review tagging, comment summarization, and change detection.

Marketing Technology & Content Operations Automation:
  • Design and automate workflows across Veeva PromoMats / Vault (VAE generation, metadata validation, reference linking), Veeva CRM (VAE send, audience targeting, testing), Salesforce Marketing Cloud (SFMC) email builds, dynamic content testing, and deployments, Adobe Journey Optimizer (AJO) journey setup, testing, and email operationalization.
  • Enhance operational efficiency through automated asset packaging and trafficking, compliance metadata validation, automated broken-link and rendering checks, IVA build and update validation scripts.

Quality Assurance & Compliance Support:
  • Lead manual + automated quality control aligned to Lilly's standards, including content accuracy, regulatory compliance elements (ISI, footnotes, references, claims alignment), channel-specific formatting (email, IVA, PDF, banner), rendering across devices, browsers, CRM platforms.
  • Support audit readiness and documentation for automated processes to remain compliant with Life Sciences regulations.

Content Production & Delivery Support:
  • Perform manual PDF creation when automated GTS workflows cannot produce compliant output.
  • Oversee and automate banner trafficking, including file format validation, tracking parameter insertion (UTMs, platform tags), platform-readiness auditing.

Required Qualifications:
  • Bachelor's or Master's in Computer Science, Engineering, Data Science, AI/ML, or similar.
  • 4+ years experience in AI development, automation, or MarTech engineering-preferably within Life Sciences.
  • Hands-on experience with Python, JavaScript/TypeScript, AI/ML frameworks (OpenAI, Azure OpenAI, TensorFlow, PyTorch), Veeva Vault PromoMats & Veeva CRM, SFMC, Adobe Experience Cloud, AJO, PDF processing tools (PyPDF2, PDFMiner, OCR libraries).

Preferred Qualifications:
  • Prior work supporting pharmaceutical content supply chains, digital factories, or global production teams.
  • Experience automating VAE builds, IVA QC, SFMC dynamic content validation, Veeva metadata validation.

Core Competencies:
  • Strong understanding of pharma compliance and digital content governance.
  • Ability to translate regulatory and process requirements into scalable automation.
  • Excellent stakeholder management skills-able to partner with brand teams, MLR, analytics, and technology groups.
  • High attention to detail and quality-first mindset.
  • Ability to operate in a global, matrixed organization.