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Generative Ai Testing Jobs in Portland, OR (NOW HIRING)

Deloitte

CyberArk Senior Consultant

Portland, OR

Experience designing, developing, deploying, implementing, or supporting AI, Generative AI, or ... testing frameworks such as JUnit, Mockito, or equivalent, and with automated testing and CI/CD ...

Deloitte

AI and Data Science Engineer III

Portland, OR · On-site +1

$121K - $145K/yr

... and generative artificial intelligence solutions. * Partner with the Lead AI Solutions Architect ... Implement privacy, access, quality, lineage, monitoring, observability, testing, deployment, and ...

Deloitte

Senior Full Stack Engineer

Portland, OR · On-site

Lead requirement analysis, component design, development, unit testing, integrations, and support ... Generative AI Solutions and/or Agentic AI Framework (Langraph, Google Development kit, etc.) • ...

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All JobsGenerative Ai Testing JobsGenerative Ai Testing Jobs in Portland, OR

Generative Ai Testing information

See Portland, OR salary details

$33

$56

$81

How much do generative ai testing jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for generative ai testing in Portland, OR is $56.98, according to ZipRecruiter salary data. Most workers in this role earn between $46.92 and $65.24 per hour, depending on experience, location, and employer.

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 much do AI testers get paid?

AI testers, involved in evaluating and validating generative AI models, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in machine learning and data analysis can earn higher wages.

Is AI testing a good career?

AI testing, including roles like Generative AI Testing, is a growing field with increasing demand for skills in machine learning, data analysis, and programming. It offers opportunities in tech companies, research labs, and startups, often requiring knowledge of AI frameworks and testing tools. The career can be stable and rewarding for those with technical expertise and an interest in AI development and quality assurance.

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 a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or executive positions, often requiring advanced skills, extensive experience, and sometimes specialized certifications. These roles usually involve leading AI development projects, strategic planning, and overseeing AI teams in large organizations or tech companies.

How do I become an AI tester?

To become an AI tester, you should have a strong understanding of machine learning concepts, programming skills in languages like Python, and experience with data annotation and model evaluation. Familiarity with AI development tools and testing frameworks, along with attention to detail, is essential for identifying issues in AI systems.

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 Portland, OR? For Generative Ai Testing jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Portland, OR look for? The top searched job categories for Generative Ai Testing jobs in Portland, OR are:
Generative Ai Testing jobs near you
AI-forward Software Engineer

AI-forward Software Engineer

JS Consulting

Beaverton, OR • On-site

Contractor

Posted 6 days ago

Job description

Job Title- AI-forward Software Engineer

Project Location – (Remote + international travel) (expenses paid by client for the international travel)

Duration- 6+ months contract

Visa- USC/ GC/ GCEAD/ H4EAD

Must have Valid LinkedIn profile.

Job Description-: This is a unique position as it'll require hands-on coding in BOTH GitHub Copilot AND Amazon Q, previous mentorship/training experience (think: paired programming, or DevRel type work), and will very likely require international travel (India is confirmed as a primary location, possibly Europe and, South America). 
These individuals will be supporting ~50 engineers, over 2-week sprints. for a total of 30 weeks. The rotation, work schedule, and travel plans are all up in the air, so we need to talk to contractors that'll be flexible. 

GitHub Copilot Adoption Framework (GCAF) Collaborative Engineer (Remote + international travel)

We are seeking an AI-forward Software Engineer with expert-level knowledge of GitHub Copilot and Amazon Q features. With both hands-on experience, and mentoring capabilities, this individual will design and deliver structured hands-on developer sprints centered around AI.
This contractor opportunity is likely to include international travel for an extended period of time (potentially 4-6 weeks). For more details, please review the description below.

 Key Responsibilities

  • Design and deliver structured, hands-on developer sprints focused on GitHub Copilot and Amazon Q.
  • Facilitate live coding sessions, demonstrations, and collaborative labs.
  • Mentor developers through real-world challenges, providing guidance on prompt engineering, debugging, and feature implementation.
  • Develop and maintain instructional materials, including curriculum, documentation, and best-practice guides.
  • Adapt instructional strategies based on participant feedback and learning progress.
  • Promote responsible AI usage, including security, ethics, and data privacy considerations.

 Required Skills & Proficiencies

  • Generative AI & Tool Expertise, including MCP usage and Agentic Orchestration
  • Expert-level knowledge of GitHub Copilot and Amazon Q features, including Copilot Chat agents and Amazon Q’s /dev command.
  • Advanced prompt engineering skills for both platforms.
  • Understanding of Copilot Enterprise and Amazon Q for Business, including RAG and internal codebase reasoning.
  • Intermediate understanding of LLM fundamentals, AI ethics, and security practices.
  • Strong problem-solving mindset and diagnostic skills.
  • Passion for generative AI and developer enablement.

 Instructional & Communication Skills

  • Advanced curriculum development and public speaking abilities.
  • Expert-level live coding and demonstration skills.
  • Strong mentoring and facilitation capabilities.
  • Intermediate technical writing skills for post-sprint resources.

 Technical & Development Skills

  • Advanced proficiency in at least one of Python, JavaScript/TypeScript, or Java.
  • Expert fluency with IDEs such as VS Code and JetBrains.
  • Deep understanding of GitHub Flow, Agile practices, and version control.
  • Intermediate knowledge of cloud and DevOps fundamentals (AWS, IaC, CI/CD).
  • Strong grasp of testing and debugging strategies.

 Preferred Qualifications:

  • Certifications in cloud platforms (e.g., AWS) or DevOps practices.
  • Contributions to open-source or developer communities.
  • Patience, empathy, and adaptability in instructional settings.