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Senior Artificial Intelligence Testing Jobs (NOW HIRING)

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Senior Artificial Intelligence Testing information

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$25K

$80.3K

$163.5K

How much do senior artificial intelligence testing jobs pay per year?

As of Jun 20, 2026, the average yearly pay for senior artificial intelligence testing in the United States is $80,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Artificial Intelligence Testing professional, and why are they important?

To thrive as a Senior Artificial Intelligence Testing professional, you need expertise in software testing methodologies, machine learning concepts, and proficiency in programming languages like Python, along with a degree in computer science or a related field. Familiarity with AI testing frameworks, automated testing tools (such as TensorFlow, PyTorch, Selenium), and relevant certifications (like ISTQB) is often required. Strong analytical thinking, attention to detail, and effective communication skills distinguish top performers in this role. These competencies are critical to ensuring the quality, reliability, and ethical integrity of AI systems in complex, real-world applications.

What are Senior Artificial Intelligence Testing professionals?

Senior Artificial Intelligence Testing professionals are experienced specialists responsible for designing, executing, and overseeing tests to ensure the quality, reliability, and ethical standards of AI systems. They develop test plans, create testing frameworks, and analyze AI model behaviors to identify errors, biases, or security vulnerabilities. They often collaborate with data scientists, engineers, and product managers to refine AI algorithms and ensure they perform as intended in real-world scenarios. Their role is critical in maintaining trust and safety in AI-driven products and services.

What is the highest paying job in artificial intelligence?

The highest paying roles in artificial intelligence often include AI research directors, machine learning engineers, and AI solutions architects, with senior positions earning six-figure salaries or more. These roles typically require advanced degrees, extensive experience, and expertise in deep learning, natural language processing, or computer vision, along with proficiency in tools like TensorFlow or PyTorch.

Is AI testing a good career?

AI testing is a growing field within artificial intelligence roles, focusing on evaluating AI systems for accuracy, reliability, and safety. It requires skills in programming, data analysis, and understanding AI models, often involving tools like Python and machine learning frameworks. The demand for AI testers is increasing as AI applications expand across industries, making it a promising career path for those with technical expertise.

How much do AI testers get paid?

AI testers typically earn between $70,000 and $120,000 annually, depending on experience, location, and industry. Senior AI testing roles often offer higher salaries and may require knowledge of machine learning frameworks and testing tools.

What are some common challenges faced by Senior Artificial Intelligence Testing professionals, and how can they be addressed?

Senior Artificial Intelligence Testing professionals often encounter challenges such as ensuring the reliability of complex AI models, dealing with insufficient or biased data, and validating unpredictable outputs. Addressing these issues typically involves developing comprehensive test plans, employing advanced testing frameworks, and collaborating closely with data scientists and engineers. Regular communication with cross-functional teams and staying updated on the latest AI testing methodologies are also essential for overcoming these challenges and ensuring robust, ethical AI systems.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior AI researchers, machine learning directors, or AI executives, often requiring advanced skills in data science, programming, and deep learning. These positions usually involve leadership, strategic planning, and extensive experience, and they may include bonuses or stock options that contribute to the total compensation package.

What is the difference between Senior Artificial Intelligence Testing vs Machine Learning Engineer?

AspectSenior Artificial Intelligence TestingMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, experience in AI testing toolsBachelor's or Master's in CS, strong programming skills, knowledge of ML frameworks
Work EnvironmentAI development teams, quality assurance, testing labsData science teams, software development environments, cloud platforms
Employer & Industry UsageTech companies, AI-focused firms, research institutionsTech companies, startups, research labs, AI product companies
Common Search & Comparison IntentUnderstanding testing roles in AI projectsDeveloping and deploying machine learning models

While Senior Artificial Intelligence Testing focuses on evaluating and validating AI systems for accuracy and reliability, Machine Learning Engineers design, build, and optimize machine learning models. Both roles require a strong background in computer science and AI, but their core responsibilities differ: testing emphasizes quality assurance, whereas engineering emphasizes model development and deployment.

More about Senior Artificial Intelligence Testing jobs
What cities are hiring for Senior Artificial Intelligence Testing jobs? Cities with the most Senior Artificial Intelligence Testing job openings:
What are the most commonly searched types of Artificial Intelligence Testing jobs? The most popular types of Artificial Intelligence Testing jobs are:
What states have the most Senior Artificial Intelligence Testing jobs? States with the most job openings for Senior Artificial Intelligence Testing jobs include:
Infographic showing various Senior Artificial Intelligence Testing job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.
Senior Artificial Intelligence Data Engineer

Senior Artificial Intelligence Data Engineer

Vizient, Inc.

Chicago, IL

$109K - $148K/yr

Other

Posted 9 days ago


Job description

When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Summary In this role, you will help build and enhance a modern, AI-ready data enablement platform that supports cross-domain analytics, governed data products, and reusable engineering patterns across the enterprise. You will enable data producers and analytics teams through guided pathways, reusable accelerators, metadata-driven frameworks, CI/CD patterns, Databricks Asset Bundles, dbt transformation standards, Unity Catalog governance, and Starburst/Trino analytical access. You will focus on helping teams create trusted, governed, reusable, and AI-ready derivative data products that support analytics, reporting, GenAI, semantic search, and emerging agentic platform use cases.

As a hands-on senior individual contributor, you will combine platform engineering, data transformation, governance, and enablement to drive scalable and repeatable data product delivery across the organization. Responsibilities Build and support scalable data engineering solutions using Azure Databricks, PySpark, SQL, Delta Lake, Azure Data Factory, dbt, and Unity Catalog. Improve metadata-driven Azure Data Factory and Databricks patterns for orchestration, configuration, monitoring, restartability, and operational support.

Develop reusable accelerators including CI/CD templates, Databricks Asset Bundle patterns, deployment automation, environment configuration, and data product onboarding templates. Design, develop, and support dbt models, macros, tests, documentation, and transformation standards for governed analytical data products. Provide guidance on appropriate technology selection and implementation patterns across dbt, Databricks notebooks and workflows, Delta Live Tables, Spark, and Starburst/Trino.

Support cross-domain analytics initiatives by transforming source-refined data into trusted, reusable, business-aligned derivative data products. Leverage Unity Catalog to establish and support governed catalogs, schemas, tables, lineage, access controls, naming standards, and certification practices. Support Starburst/Trino as an analytical and federated query layer for governed enterprise data consumption.

Apply Azure DevOps, Git, CI/CD, and Infrastructure as Code (IaC) practices to create repeatable, testable, and environment-aware platform delivery processes. Troubleshoot and resolve production issues related to orchestration, transformations, data quality, access management, query performance, deployments, and operational workflows. Collaborate with data engineering, analytics, platform, governance, and business teams to establish reusable, scalable, and supportable data engineering patterns.

Contribute to the evolution of enterprise data engineering standards, governance practices, observability capabilities, and AI-ready data product frameworks. Qualifications Relevant degree preferred. 5 or more years of hands-on data engineering experience building production-grade data platforms, pipelines, or analytical data products required.

Strong experience with Azure Databricks, PySpark, Spark SQL, Delta Lake, Azure Data Factory, SQL, and dbt required. Experience with Azure DevOps, Git, pull request workflows, CI/CD pipelines, and release management practices required. Working knowledge of lakehouse architecture, metadata management, data governance, lineage, access control, and operational support required.

Demonstrated ability to function as a senior individual contributor with strong ownership, technical judgment, and cross-functional collaboration skills required. Experience supporting enterprise-scale analytical platforms and governed data product delivery preferred. Experience with Unity Catalog, Starburst/Trino, Pulumi or other Infrastructure as Code tools, Databricks Asset Bundles, Apache Iceberg concepts, and AKS/Kubernetes-based platform operations preferred.

Experience building reusable frameworks, accelerators, templates, or platform capabilities for engineering teams preferred. Experience preparing governed structured data for AI/ML, GenAI, Retrieval-Augmented Generation (RAG), semantic search, copilots, or agentic workflows preferred. Experience within healthcare, analytics, supply chain, finance, or other regulated enterprise environments preferred.

Strong problem-solving, communication, and collaboration skills with the ability to influence technical direction and establish best practices preferred. You must be authorized to work in the United States without sponsorship. #LI-JB1 Estimated Hiring Range: At Vizient, we consider skills, experience, and organizational needs in our compensation approach.

Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $102,400.00 to $179,000.00

This position is also incentive eligible. Vizient has a comprehensive benefits plan. Please view our benefits here: http://www.vizientinc.com/about-us/careers Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.