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Generative Ai Testing Jobs (NOW HIRING)

SelectMinds

AI Architect Agentic Generative AI

Dallas, TX · On-site

$62.50 - $82.50/hr

... testing. Collaborate with platform and DevOps teams to enable governed AWS landing zones, CI/CD ... AI/ML or generative AI solutions in production environments. Hands-on experience with Amazon ...

Peraton

Generative AI Engineering Intern (Graduate)

$17.25 - $22.25/hr

Support prompt engineering efforts including designing, testing, and refining prompts to improve ... Conduct research on emerging generative AI techniques, foundation models, and best practices ...

Johnson & Johnson

Data and Generative AI Engineer

Raritan, NJ · On-site

$117K - $140K/yr

Design, develop and deliver Generative/Agentic AI solutions that accelerate End-to-End Data ... Ensure data quality and integrity through meticulous testing and validation, applying Intelligent ...

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for generative ai testing in the United States is $53.73, according to ZipRecruiter salary data. Most workers in this role earn between $44.23 and $61.54 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.
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Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $111,750 per year, or $53.7 per hour.

Technical Lead - Generative AI (GenAI) Solutions

Interon IT Solutions

Houston, TX • On-site

Contractor

Posted 10 days ago

Job description

Job Title: Technical Lead – Generative AI (GenAI) Solutions

Location: Houston, TX (Onsite)
Contract Type-W2

Job Description

We are looking for a Technical Lead – Generative AI (GenAI) Solutions to lead the design, development, and delivery of enterprise-grade AI solutions. The ideal candidate will have strong hands-on engineering experience, proven technical leadership, and deep knowledge of AI/ML systems, agent architectures, and modern microservices platforms. This role requires close collaboration with product managers, engineering leaders, and business stakeholders.

Key Responsibilities

  • Lead end-to-end technical delivery of Generative AI solutions, including AI agents, RAG pipelines, and automation components.
  • Translate business and product requirements into scalable technical designs and implementations.
  • Own technical architecture, design decisions, and engineering standards across the pod/team.
  • Participate in sprint planning, backlog grooming, and technical discovery sessions.
  • Conduct code reviews, manage module ownership, and ensure adherence to best practices.
  • Track delivery metrics including velocity, quality, and performance.
  • Drive A/B testing, experimentation, and continuous improvement initiatives.
  • Mentor and support junior engineers (SDE I and SDE II).
  • Collaborate with Product Managers, Tech Chapter Leads, and Engagement Leads to align solutions with platform strategy.
  • Communicate technical updates and risks to business and technical stakeholders.
  • Represent the team in architecture reviews and technical forums.

Required Skills & Qualifications

Technical Leadership & Engineering

  • 8+ years of software engineering experience with at least 2+ years in a technical lead role.
  • Strong experience in client-side and backend development, including service orchestration and streaming.
  • Expertise in microservices architecture and enterprise AI/ML platforms.
  • Experience with API design, service integrations, and cross-platform communication.
  • Proficiency with CI/CD pipelines, version control, and automated deployments.

Generative AI & Agent Systems

  • Hands-on experience designing and developing Generative AI applications.
  • Experience building conversational AI, autonomous agents, and multi-agent systems.
  • Strong understanding of Retrieval-Augmented Generation (RAG) architectures.
  • Experience with inference strategies and model selection trade-offs (cloud-based vs on-device).

Security & Compliance

  • Knowledge of enterprise data privacy, cybersecurity standards, and regulatory requirements.
  • Experience handling user interaction data, logs, observability, and retention policies.

Testing & Observability

  • Experience with observability tools for logging, monitoring, and distributed tracing.
  • Strong understanding of API testing, authentication, and authorization mechanisms.

Preferred Qualifications

  • Experience delivering AI solutions in large-scale enterprise environments.
  • Exposure to data science, automation, or ML engineering workflows.
  • Strong communication skills with the ability to translate technical concepts to non-technical stakeholders.