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Generative Ai Testing Jobs in Arizona (NOW HIRING)

Photon

AI Dev (Features + CHQ)_Tempe,AZ

Phoenix, AZ

Work with Generative AI services, LLM APIs, semantic search, and workflow orchestration platforms ... Support debugging, monitoring, testing, and production issue resolution activities. Qualifications ...

Lorven Technologies

AI Engineering Leader

Tempe, AZ · On-site

$98K - $129K/yr

... Generative AI, Agentic systems, and production-grade AI platforms. This role i not a pure ... Automated deployment Testing and validation of AI systems Continuous monitoring and iteration AI ...

BTree Solutions, Inc.

AI MANAGER

Vail, AZ · On-site

Ensures documentation, version control, testing protocols, and deployment pipelines meet ... generative AI, predictive modeling, and data analysis. * Knowledge and understanding of research ...

KUBRA

AI Engineer

Tempe, AZ · Hybrid

This role spans applied AI (including generative AI and LLM-based systems), production-grade ... Strong software engineering fundamentals, including experience with CI/CD, testing practices, and ...

KUBRA

AI Engineer

Tempe, AZ · Hybrid

This role spans applied AI (including generative AI and LLM-based systems), production-grade ... Strong software engineering fundamentals, including experience with CI/CD, testing practices, and ...

KUBRA

AI Engineer

Tempe, AZ · On-site

This role spans applied AI (including generative AI and LLM-based systems), production-grade ... Strong software engineering fundamentals, including experience with CI/CD, testing practices, and ...

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Generative Ai Testing information

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

What are the key skills and qualifications needed to thrive as a Generative AI Testing Specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What is Generative AI Testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.
What are popular job titles related to Generative Ai Testing jobs in Arizona? For Generative Ai Testing jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Arizona look for? The top searched job categories for Generative Ai Testing jobs in Arizona are:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Arizona as of June 2026, with employment types broken down into 10% Internship, 71% Full Time, 14% Part Time, and 5% Temporary. Highlights an 80% In-person, 5% Hybrid, and 15% Remote job distribution.
AI Dev (Features + CHQ)_Tempe,AZ

AI Dev (Features + CHQ)_Tempe,AZ

Photon

Phoenix, AZ

Other

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

Job description

AI Developer (Features + CHQ)

Photon is seeking a skilled AI Developer (Features + CHQ) to support the development and enhancement of AI-powered features for Tulip AI, Dutch Bros' unified employee support platform.

This role focuses on building intelligent user-facing capabilities and enterprise productivity features for the CHQ (Corporate HQ) platform, enabling corporate teams to streamline workflows, improve operational efficiency, and enhance employee support experiences through AI-driven interactions and automation.

The AI Developer will work closely with product, platform, frontend, backend, and AI engineering teams to develop scalable AI-enabled features, integrate enterprise systems, and deliver seamless user experiences across web and desktop applications. The ideal candidate should have strong experience in application development, AI integrations, API consumption, and enterprise workflow enablement.

Responsibilities

  • Design, develop, and enhance AI-powered features for the CHQ platform and Tulip AI ecosystem.
  • Build user-centric workflows, productivity tools, and intelligent automation capabilities for corporate users.
  • Integrate frontend applications with backend APIs, AI services, and enterprise systems.
  • Develop AI-assisted user experiences including conversational workflows, recommendations, and intelligent task support.
  • Work with Generative AI services, LLM APIs, semantic search, and workflow orchestration platforms.
  • Collaborate with backend and platform teams to integrate APIs, authentication, and enterprise data sources.
  • Implement scalable, reusable, and maintainable application components and feature modules.
  • Support enterprise workflow automation and operational productivity initiatives.
  • Ensure application responsiveness, usability, performance, and reliability.
  • Participate in Agile development processes including sprint planning, feature estimation, and technical discussions.
  • Write clean, testable, and maintainable code following engineering best practices.
  • Support debugging, monitoring, testing, and production issue resolution activities.

Qualifications

Need to Have

  • 4+ years of experience in application development or feature engineering.
  • Strong experience in frontend or full-stack application development.
  • Experience integrating AI services, LLM APIs, or Generative AI-powered features.
  • Strong understanding of REST APIs, frontend-backend integration, and asynchronous workflows.
  • Experience working with modern frontend frameworks such as React, Angular, or similar technologies.
  • Familiarity with enterprise application architecture and workflow-based platforms.
  • Knowledge of authentication, authorization, and secure application development practices.
  • Experience with Agile development methodologies and Git-based workflows.
  • Strong problem-solving, debugging, and communication skills.

Good to Have

  • Experience with enterprise productivity platforms or internal business applications.
  • Exposure to conversational AI, workflow automation, or AI assistant platforms.
  • Familiarity with Python, FastAPI, or backend service integrations.
  • Experience with semantic search, RAG architectures, or vector databases.
  • Exposure to cloud platforms such as AWS, Azure, or GCP.
  • Experience in QSR, retail, hospitality, or large-scale enterprise environments.
  • Knowledge of analytics, monitoring, and observability tools.
  • Experience collaborating in co-development or distributed engineering models.

Compensation, Benefits and Duration

Minimum Compensation: USD 56,000 Maximum Compensation: USD 196,000 Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role. Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees. This position is available for independent contractors No applications will be considered if received more than 120 days after the date of this post.

Job Info
  • Job Identification 26063
  • Locations Anthem, Arizona, US

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