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Manager Ai Qa Jobs (NOW HIRING)

Jobgether

$6 - $65/hr

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI QA Trainer - LLM Evaluation based in Netherlands. This role offers ...

Saransh Inc

Conversational AI QA Lead

Irving, TX · On-site

- Conversational AI QA Lead - chatbots Locations: Irving/Dallas, Texas FULL TIME Day to Day job ... Collaborate with product management, engineering, and operations teams to define quality metrics ...

Introlligent Inc.

QA

Cupertino, CA · On-site

$51 - $69.50/hr

AI Test Automation Engineer Location: Cupertino, CA or Austin, TX (Hybrid - Tue/Wed/Thu Onsite ... A solid QA automation background is required. Key Responsibilities * Lead AI quality and ...

Introlligent Inc.

QA

Austin, TX · On-site

$41 - $55.75/hr

AI Test Automation Engineer Location: Cupertino, CA or Austin, TX (Hybrid - Tue/Wed/Thu Onsite ... A solid QA automation background is required. Key Responsibilities * Lead AI quality and ...

Vizient

Senior AI Quality & Reliability Engineer

Chicago, IL · On-site

$91K - $123K/yr

... management, issue tracking, release readiness, risk identification, and production support ... Experience supporting Quality Engineering or Quality Assurance across enterprise platforms, APIs ...

State Street

AI QA Engineer, AVP

Burlington, MA · On-site

Responsibilities : • Partner closely with product managers, software engineers, architects, and ... reusable QA frameworks and test approaches tailored to validating AI-driven functionality ...

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How much do manager ai qa jobs pay per year?

As of Aug 4, 2026, the average yearly pay for manager ai qa in the United States is $118,074.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $144,500.00 per year, depending on experience, location, and employer.

How does a Manager AI QA typically collaborate with data scientists and software engineers during the development lifecycle?

A Manager AI QA works closely with both data scientists and software engineers to ensure the quality and reliability of AI models and systems. During development, they help define testing strategies, review model validation procedures, and facilitate communication across teams to address potential issues early. They often coordinate the creation of test datasets, oversee automated testing pipelines, and provide feedback to improve model robustness. This collaborative environment helps ensure that AI solutions meet both functional and ethical standards before deployment.

What does a Manager AI QA do?

A Manager AI QA (Artificial Intelligence Quality Assurance) oversees the testing and quality assurance processes for AI-based products and solutions. They lead teams responsible for identifying defects, ensuring model accuracy, and validating performance metrics. Their role includes developing QA protocols specific to AI, coordinating with data scientists and engineers, and implementing best practices to maintain high-quality AI systems. They also stay updated on emerging AI testing methodologies and tools to ensure projects meet industry standards.

What are the key skills and qualifications needed to thrive as a Manager AI QA?

To thrive as a Manager AI QA, you need a strong background in software quality assurance, AI/ML concepts, and leadership, typically supported by a degree in computer science or related fields. Familiarity with QA automation tools (like Selenium or Appium), AI testing frameworks, and experience with cloud platforms and version control systems is important. Exceptional communication, problem-solving skills, and the ability to lead cross-functional teams set standout candidates apart. These skills ensure rigorous testing of AI solutions, drive process improvements, and help teams deliver robust, reliable AI products.
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Infographic showing various Manager Ai Qa job openings in the United States as of July 2026, with employment types broken down into 67% Full Time, 22% Part Time, and 11% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution, with an average salary of $118,074 per year, or $56.8 per hour.

AI QA Trainer - LLM Evaluation

Jobgether

Remote

$6 - $65/hr

Contractor

Medical, PTO

Posted 11 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI QA Trainer - LLM Evaluation based in Netherlands.

This role offers the opportunity to contribute directly to the evolution of advanced AI systems by improving their reliability, accuracy, and safety.
You will work on evaluating large language models through structured testing, quality analysis, and adversarial scenarios.
The position combines AI quality assurance, data evaluation, and technical problem-solving to strengthen model performance.
You will design evaluation frameworks, identify failure patterns, and help improve AI reasoning capabilities across diverse use cases.
Working with cutting-edge AI technologies, you will influence how future systems handle information, reasoning, and real-world tasks.
This is a remote contract opportunity for professionals passionate about AI quality, testing, and responsible model development.

Accountabilities:

The role focuses on ensuring the quality, reliability, and safety of advanced AI models through comprehensive evaluation and testing processes. You will collaborate on identifying weaknesses, improving evaluation methodologies, and creating actionable insights that enhance model performance.

  • Evaluate large language models across areas such as factual accuracy, reasoning quality, hallucination detection, safety, and reliability.
  • Design and execute test plans, regression suites, and evaluation frameworks to measure model performance.
  • Identify and document model failures, including prompt vulnerabilities, incorrect outputs, bias issues, and reasoning inconsistencies.
  • Develop clear evaluation rubrics, pass/fail criteria, and quality benchmarks for AI system assessment.
  • Perform adversarial testing, red-teaming exercises, and robustness evaluations to identify potential risks.
  • Verify grounding, retrieval-augmented generation outputs, tool usage accuracy, and workflow reliability.
  • Analyze model behavior and provide recommendations for improving prompts, guardrails, and evaluation strategies.
  • Support automation initiatives using tools such as Python or SQL to improve testing efficiency.
  • Maintain detailed documentation of findings, root-cause analysis, and reproducible issue reports.
  • Collaborate with technical teams to improve AI evaluation metrics, dashboards, and quality monitoring processes.
Requirements:

The ideal candidate brings strong experience in AI quality assurance, machine learning evaluation, software testing, or related technical disciplines. You should be comfortable analyzing complex AI behaviors and communicating technical findings clearly.

  • Bachelor's, Master's, or PhD in Computer Science, Data Science, Computational Linguistics, Statistics, or a related technical field preferred.
  • Experience testing, evaluating, or validating AI/ML systems, particularly large language models.
  • Strong understanding of LLM evaluation concepts, including hallucination detection, factual consistency, safety testing, and reliability analysis.
  • Experience designing QA frameworks, evaluation criteria, regression testing processes, or quality benchmarks.
  • Familiarity with prompt engineering, system prompts, retrieval-augmented generation (RAG), and AI safety practices.
  • Experience with adversarial testing, red teaming, bias assessment, or compliance-oriented AI reviews.
  • Knowledge of test automation tools and programming languages such as Python or SQL.
  • Familiarity with LLM evaluation tools, experiment tracking platforms, or AI testing frameworks.
  • Strong analytical skills with the ability to identify patterns, investigate failures, and propose improvements.
  • Excellent written and verbal communication skills, with the ability to clearly explain technical reasoning and findings.
Benefits:
  • Competitive contractor compensation ranging from $6 to $65 per hour, depending on experience, expertise, and geographic location.
  • Fully remote work environment with flexibility to contribute from anywhere.
  • Opportunity to work on advanced AI systems and influence the development of future AI capabilities.
  • Hands-on exposure to cutting-edge language models, evaluation methodologies, and AI safety practices.
  • Ability to apply your technical expertise to impactful real-world AI improvement projects.
  • Flexible contract-based opportunity designed for experienced AI and QA professionals.
  • Contractors provide their own secure computer and high-speed internet connection.
  • Company-sponsored benefits such as health insurance and paid time off are not included for this contract role.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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