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Ai Automation Testing Jobs in Oklahoma (NOW HIRING)

MIRATECH Corporation

AI and Automation Lead

Tulsa, OK · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Incorporate generative AI capabilities into overall automation solutions using SDKs and MCP servers ... Establish standards for architecture, testing, monitoring, documentation, releases, and support

MIRATECH Corporation

AI and Automation Lead

Tulsa, OK · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Incorporate generative AI capabilities into overall automation solutions using SDKs and MCP servers ... Establish standards for architecture, testing, monitoring, documentation, releases, and support

MIRATECH Corporation

AI and Automation Lead

Tulsa, OK · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... automation and AI capabilities across the organization. What You'll Do:Design, build, deploy, and ... architecture, testing, monitoring, documentation, releases, and supportEnforce governance ...

Deloitte

System Test and Validation Lead

Tulsa, OK · On-site +1

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 ...

Deloitte

System Test and Validation Lead

Tulsa, OK · On-site +1

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 ...

Deloitte

System Test and Validation Lead

Tulsa, OK · On-site +1

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 ...

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All JobsAi Automation Testing JobsAi Automation Testing Jobs in Oklahoma

Ai Automation Testing information

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 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 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 Oklahoma? For Ai Automation Testing jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Ai Automation Testing jobs in Oklahoma look for? The top searched job categories for Ai Automation Testing jobs in Oklahoma are:
What cities in Oklahoma are hiring for Ai Automation Testing jobs? Cities in Oklahoma with the most Ai Automation Testing job openings:
Ai Automation Testing jobs near you

AI/Automation Architect

Norman Regional Health System

Norman, OK • On-site

Full-time

Re-posted 23 days ago

Norman Regional Health System rating

7.4

Company rating: 7.4 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

268th of 887 rated healthcare providers

Job description

Job Summary
The AI & Automation Architect is responsible for designing the end-to-end technical strategy for the organization's intelligent automation initiatives. This role involves selecting the right mix of technologies (RPA, Generative AI, Machine Learning, IDP) to solve complex business problems. The Architect ensures that solutions are scalable, secure, and cost-effective, moving beyond simple task automation to full-scale process transformation.
  • Design scalable architectures for intelligent automation solutions, integrating RPA bots with AI models (e.g., using LLMs for decision-making within an RPA workflow)
  • Evaluate and select appropriate platforms and tools based on cost, security, and fit
  • Define how automation tools communicate with enterprise systems via APIs, webhooks, or database connections
  • Establish coding standards, reusable component libraries, and best practices for development teams to ensure consistency
  • Work with InfoSec to ensure all AI/automation workflows comply with data privacy laws (GDPR/CCPA/HIPAA) and internal security policies (e.g., PII masking, role-based access control)
  • Oversee the infrastructure sizing to support bots and high-volume AI inference requests
  • Collaborate with business analysts to determine if a process should be automated and how
  • Lead rapid Proof of Concept (PoC) projects to test emerging technologies before enterprise rollout
  • Design the "Control Room" strategy for monitoring bot health, AI model drift, and license utilization
  • Disaster Recovery: Create failover strategies to ensure business-critical automations continue running during system outages

Typical Duties:
  • Meeting with Health system leaders to analyze a proposed process and determining if it requires simple RPA, complex AI (e.g., OCR/NLP), or if it shouldn't be automated at all
  • Drafting technical blueprints that detail exactly how a bot will log in, where data will be stored, how exceptions are handled, and which AI models will be called
  • Researching and testing new AI tools to see if they fit the health systems tech stack better than current tools
  • Designing and documenting the REST/SOAP API integrations between the automation platform and third-party apps
  • Calculating the necessary compute power (CPU/RAM/GPU) required for upcoming automations and provisioning Virtual Machines (VMs)
  • Configuring "Credential Vaults" so bots can log into systems without exposing passwords in the code
  • Building and maintaining a library of "snippets" that all developers must use to save time
  • Monitors bot health to ensure critical automations ran successfully overnight
  • Troubleshoot complex failures that regular support teams cannot fix
  • Planning and executing upgrades for the automation platform without breaking existing bots
  • Facilitating whiteboard sessions with non-technical departments to uncover their pain points
  • Prompt engineering for business logic, understanding "context windows," and mitigating AI hallucinations in enterprise data.
  • Experience with OCR and data extraction tools.
  • Python, C#/.NET
  • PowerShell or Bash for infrastructure tasks.
  • Ability to design solutions that can handle spikes in volume.
  • Knowledge of load balancing and concurrent processing.
  • Understanding of RBAC (Role-Based Access Control).
  • Secure credential management.
  • Understanding of Virtual Machines (VMs), VDI (Virtual Desktop Infrastructure), and Docker/Kubernetes.
  • Setting up pipelines to automate the testing and deployment of bots.
  • Version control (Git) strategies for automation teams.

Qualifications
Education
  • Bachelor's degree in Computer Science, Data Science, or a related engineering discipline or equivalent experience required.

Licensure/Certification
  • Prefer candidate holds an advanced professional certification in a major automation platform, such as the UiPath Certified Professional Automation Solutions Architect or Microsoft Power Platform Solution Architect

(Above requirements can be met by equivalent combination of education and experience)
Experience
  • 7+ years of IT experience, including at least 4 years designing scalable RPA and intelligent automation solutions using platforms like UiPath or Power Automate
  • Demonstrated expertise in integrating generative AI, machine learning models, and complex APIs into business workflows is essential
  • Proven leadership in guiding technical teams through the full software development lifecycle (SDLC) within an Agile environment is required
  • Experience translating business requirements into technical blueprints and managing stakeholder expectations is critical for success in this role

Work Shift
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What Norman Regional Health System employees say

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