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Generative Ai Testing Jobs in Arizona (NOW HIRING)

Lorven Technologies

AI Solution Architect

Tempe, AZ · On-site

$60.25 - $79.50/hr

AI Solution Architect - Agentic & Generative AI Locations: Austin, Tx | Tempe, Az | Charlotte, NC ... Testing & evaluation * Deployment * Monitoring & observability * Risk controls & governance

Infosys Limited Digital

AI Engineer

Phoenix, AZ · On-site

... testing phases to ensure error-free, clean releases. Your contribution to the team: A knack of ... Design, develop, and deploy generative AI models for various applications, such as text generation ...

Infosys Limited Digital

AI Engineer

Phoenix, AZ · On-site

... testing phases to ensure error-free, clean releases. Your contribution to the team: A knack of ... Design, develop, and deploy generative AI models for various applications, such as text generation ...

Infosys Limited Digital

AI Engineer

Phoenix, AZ · On-site

... testing phases to ensure error-free, clean releases. Your contribution to the team: A knack of ... Design, develop, and deploy generative AI models for various applications, such as text generation ...

Photon

AI Devs (Platform + BE)_Tempe,AZ

Anthem, AZ · On-site

The platform combines Generative AI, enterprise integrations, backend services, and workflow ... Contribute to CI/CD pipelines, automated testing, and engineering best practices. * Implement ...

Photon

AI Dev (Features + CHQ)_Tempe,AZ

Anthem, AZ · On-site

The platform combines Generative AI, enterprise integrations, backend services, and workflow ... Contribute to CI/CD pipelines, automated testing, and engineering best practices. * Implement ...

Photon

AI Dev (Features + CHQ)_Tempe,AZ

Anthem, AZ · On-site

The platform combines Generative AI, enterprise integrations, backend services, and workflow ... Contribute to CI/CD pipelines, automated testing, and engineering best practices. * Implement ...

Photon

AI Devs (Platform + BE)_Tempe,AZ

Anthem, AZ · On-site

The platform combines Generative AI, enterprise integrations, backend services, and workflow ... Contribute to CI/CD pipelines, automated testing, and engineering best practices. * Implement ...

Select Minds LLC

Test Automation Engineer

Phoenix, AZ · On-site

$76K - $90K/yr

... and Generative AI * Integrate MCP into AI-enabled automation workflows * Develop and maintain BDD test suites * Execute functional, regression, and API automation testing * Collaborate with ...

MY DR NOW

AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

... and Generative AI * Build intelligent agents, RAG solutions, prompt workflows, and AI-driven ... Participate in Agile development, testing, code reviews, and CI/CD practices What You Bring

Select Minds LLC

Test Automation Engineer

Phoenix, AZ · On-site

$76K - $90K/yr

... and Generative AI * Integrate MCP into AI-enabled automation workflows * Develop and maintain BDD test suites * Execute functional, regression, and API automation testing * Collaborate with ...

Tata Consultancy Service Limited

AI Engineer

Phoenix, AZ · On-site

$110K - $125K/yr

... testing and validation of unit code, in conjunction with error handling through pipelines. • ... Generative AI. • Drive discovery sprints and AI ideation efforts • Stay abreast of broad AI ...

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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.
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 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 Solution Architect

Lorven Technologies

Tempe, AZ • On-site

$60.25 - $79.50/hr

Contractor

Re-posted 26 days ago

Job description

AI Solution Architect - Agentic & Generative AI
Locations: Austin, Tx | Tempe, Az | Charlotte, NC | New York, NY - Onsite
Duration: 12 Months Contract
Role Overview
The AI Solution Architect is a senior technical leader responsible for designing, architecting, and operationalizing Agentic AI and Generative AI solutions at enterprise scale. This role is central to shaping and implementing an AI-first Product Delivery Lifecycle (PDLC), ensuring product development processes, engineering practices, and operating models are optimized for AI-native platforms, agentic systems, and rapid value iteration.
This individual will operate at the intersection of architecture, AI platform engineering, ML lifecycle management, enterprise integration, governance, and organizational transformation.
Key Responsibilities
AI Architecture & Solution Design
  • Architect enterprise-scale Agentic and Generative AI systems, including:
  • Multi-agent orchestration frameworks
  • Retrieval-Augmented Generation (RAG) pipelines
  • Autonomous task execution patterns
  • Tool-use integration frameworks
  • Establish reference architectures for an AI-first PDLC covering:
  • Design
  • Development
  • Testing & evaluation
  • Deployment
  • Monitoring & observability
  • Risk controls & governance
  • Design and implement model lifecycle pipelines including:
  • Training & fine-tuning workflows
  • Evaluation harnesses
  • Model registry & versioning
  • Continuous improvement loops
  • Embed AI capabilities into client-facing platforms, internal tooling, and operational workflows.

AI-First PDLC Transformation
  • Define architecture, tooling, and standards for an AI-native delivery lifecycle, including:
  • Prompt engineering frameworks
  • Agent design patterns
  • Automated LLM evaluation systems
  • Safety guardrails and policy enforcement
  • Data quality validation mechanisms
  • Integrate AI evaluation and governance gates into CI/CD pipelines.
  • Establish best practices to enable cross-functional teams to become AI "builders."
  • Drive adoption of AI-driven development patterns across product, engineering, design, and risk functions.

Enterprise Integration & Data Strategy
  • Design integrations between AI systems and core enterprise platforms.
  • Partner with Data Engineering teams to define:
  • Data ingestion architectures
  • Embedding & vectorization strategies
  • Feature stores
  • Real-time inference pipelines
  • Ensure architectural alignment with:
  • Cloud strategy
  • Enterprise data governance
  • Security & compliance standards

Security, Compliance & Responsible AI
  • Architect AI systems in compliance with regulatory and governance requirements.
  • Embed identity, authorization, auditing, and model-level security patterns.
  • Implement Responsible AI practices, including:
  • Transparency
  • Bias monitoring
  • Fairness evaluation
  • Performance & drift monitoring
  • Auditability

Cross-Functional Leadership
  • Partner with senior leaders across Product, Enterprise Architecture, DevSecOps, Infrastructure, and Operations.
  • Lead architectural reviews and design whiteboarding sessions.
  • Mentor engineering teams and contribute to AI architecture standards.
  • Support hiring and talent development for emerging AI roles.

Required Qualifications
  • 2+ years architecting Generative AI, Agentic AI, or ML systems at enterprise scale.
  • 6+ years experience in cloud-native architecture (AWS preferred), including:
  • Microservices
  • Kubernetes
  • Event-driven systems
  • 5+ years hands-on experience with:
  • LLMs
  • Vector databases
  • Embeddings
  • Evaluation frameworks
  • Guardrails
  • Fine-tuning
  • Orchestration frameworks
  • 8+ years experience in Python.
  • Proficiency in C#, Java, or TypeScript is a plus.
  • 6+ years experience in ML Ops, including:
  • CI/CD for ML
  • Model versioning
  • Monitoring
  • Automated evaluation

Preferred Qualifications
  • Bachelor's degree in Computer Science, Engineering, AI/ML, or equivalent experience.
  • Relevant certifications such as:
  • AWS Solutions Architect - Professional
  • AWS Machine Learning Specialty
  • Terraform Associate
  • Experience in regulated industries.
  • Experience designing AI systems under compliance constraints.

Core Competencies
  • Strategic Architecture & Systems Thinking
  • AI Fluency & Model Lifecycle Expertise
  • Experimentation & Data-Driven Decision-Making
  • Cross-Functional Collaboration
  • Innovation & Continuous Learning
Lorven technologies logo

About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

Social media

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