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Generative Ai Testing Jobs in Arizona (NOW HIRING)

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 ...

ClifyX

AI Solution Product Manager

Phoenix, AZ · On-site

... and Generative AI use cases that measurably improve acquisition funnel performance (e.g ... A/B testing, pilots, model performance metrics) to validate AI solutions and quantify business ...

Mondo

Data Scientist

Phoenix, AZ · On-site

$136K - $164K/yr

Data Scientist III (Generative AI) Location: Phoenix, AZ Start Date: ASAP Duration: Permanent ... Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess ...

Lorven Technologies

Sr Software Engineer

Phoenix, AZ · On-site

$119K - $157K/yr

Generative AI, LLMs, prompt engineering, and RAG concepts . * AI-assisted software development, testing, documentation, and code review * Will Collaborates with leaders, business analysts, project ...

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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.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Certifications in AI or data science can enhance your qualifications and improve job prospects.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development that involves evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, making it a promising career path with increasing demand as AI technologies expand. Professionals in this area can find opportunities in tech companies, research labs, and startups focused on AI innovation.

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.
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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 August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

AI Prompt Engineer - Chandler, Az

Motion Recruitment

Chandler, AZ • On-site

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job Description

A large technology organization is building out a security-focused generative AI capability and is seeking an AI Prompt Engineer in Chandler, Arizona. The team conducts research into how advanced AI models can be used to strengthen cyber-defense programs, identify technical weaknesses, and assist security teams with large-scale testing.

This role focuses on creating the prompt logic and AI orchestration layer behind those capabilities. You will translate real cybersecurity objectives into detailed instructions that enable language models to perform security-oriented tasks. Projects may involve application scanning, simulated offensive testing, external attack-surface discovery, network service analysis, and detection of improper certificate behavior. The team works across multiple model providers, so expertise with a specific LLM platform is less important than knowing how to get reliable results from advanced models.

Required Skills & Experience

  • Significant practical experience developing and refining prompts for sophisticated AI use cases
  • Cybersecurity expertise sufficient to understand and investigate technical security findings
  • Working knowledge of application vulnerabilities, malware techniques, network boundaries, and security controls
  • Software development experience; the team is open to Python, Go, .NET, and other programming backgrounds
  • Experience creating AI-driven workflows, orchestration logic, or prompt-based tooling
  • Database knowledge involving platforms such as Postgres, Elastic, or Cloud SQL
  • Ability to independently experiment, troubleshoot model behavior, and improve results

Desired Skills & Experience

  • Understanding of secure software development and application-security testing
  • Familiarity with static and dynamic vulnerability scanning
  • Offensive-security or penetration-testing knowledge
  • Experience deploying or developing applications in cloud environments
  • Kubernetes experience
  • Exposure to GKE or similar managed container platforms

What You Will Be Doing

Daily Responsibilities

  • Convert cybersecurity testing objectives into detailed prompt-driven AI workflows
  • Develop and maintain reusable harnesses that supply models with appropriate security context
  • Conduct iterative model testing to determine which prompting approaches yield the strongest results
  • Create AI-assisted techniques for examining code and running application-security assessments
  • Develop workflows focused on external exposure, network services, and perimeter risk
  • Support analysis of digital certificates and potential misuse scenarios
  • Compare results produced by different commercial and frontier AI models
  • Refine prompts based on false positives, missed findings, and model performance
  • Work alongside data and cyber teams to move discoveries from experimentation into actionable security intelligence

The Offer

  • Contract opportunity
  • Competitive hourly compensation

You will receive the following benefits:

  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Paid Time Off (PTO)
  • 401(k)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Apply