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Ai Test Engineer Jobs in Bridgeview, IL (NOW HIRING)

LogicGate ® is the leading AI GRC platform for the Enterprise, helping governance, risk, and ... Test (SDET) Location: Remote or Bellevue, WA (Hybrid), or Chicago, IL (Hybrid) About the Role As a ...

Being a Software Engineer atiManageMeans... iManage runs on trust in every release. Our automated ... An ability to critically evaluate AI-generated code and test output rather than accepting it at ...

Being a Software Engineer at iManage Means... iManage runs on trust in every release. Our automated ... An ability to critically evaluate AI-generated code and test output rather than accepting it at ...

Being a Software Engineer at iManage Means... iManage runs on trust in every release. Our automated ... Curiosity about applying AI/LLM-based tooling to test automation problems -- for example ...

About the Role Mojo Trek is seeking an IT Quality/Test Engineer I to support a data-focused testing ... Disclosure Our hiring process for this role may include a video interview using an AI-based ...

We are seeking a Lead Penetration Test Engineer with extensive experience in penetration testing ... Knowledge of AI/ML security and adversarial testing methods, including evaluating LLMs and other ...

We are seeking a Lead Penetration Test Engineer with extensive experience in penetration testing ... Knowledge of AI/ML security and adversarial testing methods, including evaluating LLMs and other ...

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Ai Test Engineer information

See Bridgeview, IL salary details

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$45

$76

How much do ai test engineer jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for ai test engineer in Bridgeview, IL is $45.18, according to ZipRecruiter salary data. Most workers in this role earn between $34.13 and $53.51 per hour, depending on experience, location, and employer.

What is an AI test engineer?

AI Test Engineers are professionals who design, develop, and execute tests to evaluate the performance, accuracy, and reliability of artificial intelligence systems and machine learning models. They work closely with data scientists and software developers to ensure AI solutions function as intended, identifying bugs, biases, and potential risks in algorithms. Their responsibilities often include creating test cases, automating test processes, and analyzing results to improve AI system quality and compliance.

What are the key skills and qualifications needed to thrive as an AI test engineer?

To thrive as an AI Test Engineer, you need a strong background in computer science, software testing methodologies, and a good understanding of machine learning concepts, often supported by a relevant degree. Familiarity with programming languages like Python, testing frameworks such as pytest, and tools like TensorFlow or PyTorch, along with certifications in software testing or AI, are typically required. Analytical thinking, attention to detail, and effective communication set top performers apart in this role. These skills and qualities are crucial for ensuring the reliability, accuracy, and ethical deployment of AI systems.

What are some common challenges AI test engineers face when validating machine learning models?

AI Test Engineers often encounter challenges such as ensuring the quality and fairness of machine learning models, identifying edge cases that the model may not handle well, and working with limited labeled data for testing. Additionally, interpreting test results can be complex due to the probabilistic nature of AI outputs, requiring close collaboration with data scientists to understand model behaviors. Effective communication and a strong foundation in both software testing and AI concepts are essential to address these challenges and ensure reliable AI solutions.

What is the difference between Ai Test Engineer vs Data Scientist?

AspectAi Test EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of testing toolsBachelor's or higher in CS, Statistics, or related; proficiency in data analysis
Work EnvironmentSoftware testing teams, AI development projectsData analysis teams, AI research projects
Employer & Industry UsageTech companies, AI startups, software firmsTech companies, finance, healthcare, research institutions
Common Search & ComparisonOften compared for roles in AI testing and quality assuranceCompared for data analysis and AI model development roles

While both roles work within AI and tech environments, Ai Test Engineers focus on testing and validating AI systems, ensuring quality and performance. Data Scientists analyze data to develop models and insights. The roles are complementary but distinct in their core responsibilities.

How do I become an AI Test Engineer?

To become an AI Test Engineer, candidates typically need a strong background in computer science, software testing, or related fields, along with knowledge of AI and machine learning concepts. Skills in programming languages such as Python or Java, experience with testing tools, and understanding of AI model evaluation are essential. Earning relevant certifications and gaining experience in software development and testing environments can also improve job prospects.

What cities near Bridgeview, IL are hiring for Ai Test Engineer jobs?

Cities near Bridgeview, IL with the most Ai Test Engineer job openings:

Infographic showing various Ai Test Engineer job openings in Bridgeview, IL as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, 3% Contract, and 1% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $93,978 per year, or $45.2 per hour.

Test Engineer (SDET)

LogicGate

Chicago, IL • On-site, Remote

Full-time

Medical, PTO

Posted 6 days ago


Job description

LogicGate® is the leading AI GRC platform for the Enterprise, helping governance, risk, and compliance teams limit surprises, strengthen resilience, augment program performance, and confidently quantify impact and business value. Built to provide a centralized view of risk and compliance, with AI intelligence woven into the platform's core, LogicGate delivers real-time insights and actionable data to help drive current business decisions, with the flexibility to scale alongside evolving business needs. Recognized as a Leader in the GRC Market, LogicGate continues to further solidify its position as a best-in-class platform.
Excited about LogicGate but not familiar with GRC?
  • GRC stands for Governance, Risk, and Compliance
  • GRC professionals help their companies manage uncertainty, act with integrity, and stay on the right side of the law.
  • The GRC market is rapidly expanding with continuous growth opportunities. The current market size was valued at $50.5 billion in 2024 and is projected to reach $104.5 billion by 2031.

Software Engineer: Test (SDET)
Location: Remote or Bellevue, WA (Hybrid), or Chicago, IL (Hybrid)
About the Role
As a Software Engineer: Test at LogicGate, you will build and scale the automated testing frameworks, pipelines, and tools that guarantee the reliability of the Risk Cloud platform. AI is central to how you work: you are expected to embed AI-driven tooling across test authoring, regression analysis, and coverage expansion to compress delivery timelines and raise the precision of everything you ship. You will design robust automation suites, expand test coverage across the ecosystem, and systematically isolate complex software regressions. This role is ideal for an engineering-focused QA professional who treats AI as a core part of their craft, takes operational ownership of quality boundaries, and establishes data-driven testing strategies across our platform.
What You'll Do
  • Automation Engineering: Design, build, and maintain scalable automated testing frameworks and end-to-end regression suites using TypeScript and Playwright, augmented by AI-driven code generation, to take validation tasks from requirements through continuous deployment.
  • Testing Pyramid Validation: Write clean, understandable automation code to validate backend APIs and integration layers, strictly adhering to the testing pyramid to ensure a highly stable and dependable deployment lifecycle.
  • Swarm Testing & Edge Cases: Actively contribute to and expand team testing efforts, systematically validating edge cases, error conditions, and happy paths while guiding the broader Engineering Department and QA Analysts on automated testability best practices.
  • Systematic Debugging: Independently diagnose and isolate test automation failures and platform defects by reading distributed system logs, analyzing API console data, and utilizing AI-powered Datadog monitoring patterns to accelerate root-cause resolution.
  • Technical Documentation: Author clear technical documentation within the codebase and Confluence, including test strategies, automation runbooks, and detailed defect reports to support collective engineering knowledge sharing.
  • Test Data Infrastructure: Work operationally with relational databases (PostgreSQL) and advanced platform data stores, utilizing AI tools to query, manage, and optimize automated test data flows.
  • Agile Collaboration: Partner cross-functionally with product managers, feature developers, QA Analysts, and DevOps in Agile sprints, accurately estimating validation effort, mapping task prioritization, and raising project dependencies or blockers daily.
  • Code Reviews & Quality Culture: Participate actively in regular peer code reviews for both application features and test suites-providing constructive design feedback and ensuring strict compliance with team quality conventions.
  • Testing Standards & Strategy: Partner with Engineering Leadership to help define department-wide QA expectations - incorporating AI governance, coverage ownership, automated-vs-manual boundaries, and documentation standards like runbooks - and translate that direction into practices the framework and broader QA function can follow.
  • QA Analyst Enablement: Partner directly with QA Analysts across squads to build their automation skills; pair on writing tests, review their automation code, and help shift their time from manual regression toward automated coverage.
  • Testing Standards & Strategy: Partner with Engineering Leadership to help define department-wide QA expectations - coverage ownership, automated-vs-manual boundaries, and documentation standards like runbooks - and translate that direction into practices the framework and broader QA function can follow.
What You Bring
Required
  • Professional Experience: 3-5 years of professional experience in software test automation, systems validation, or backend engineering within a high-growth SaaS environment.
  • Core Language Proficiency: Strong programming experience using TypeScript or a comparable scripting language, alongside practical exposure to automated testing frameworks.
  • AI-Augmented Development: Practical experience using AI coding assistants (Cursor, GitHub Copilot, Codex, or Claude Code) as part of a normal workflow-writing effective prompts, building reusable skills or custom instructions, and knowing when to trust, verify, or discard AI-generated output.
  • Testing Strategy Mastery: Deep command of Fowler's Testing Pyramid and the ability to apply it pragmatically - knowing what belongs at the unit, integration, and end-to-end layers and why - complemented by hands-on proficiency writing API tests, functional end-to-end tests, and performance tests to validate quality at every level of the stack.
  • Mentoring and Coaching: Experience coaching or upskilling less-automation-savvy testers or engineers - you multiply impact through others' skills, not just your own code.
  • Autonomous Troubleshooting: Demonstrated ability to independently debug distributed backend microservices by parsing logs and utilizing core enterprise monitoring platforms like Datadog.
Nice to Have
  • Advanced Data Infrastructure: Familiarity with validating message queues (RabbitMQ), graph databases (Neo4j), or distributed caching layers (Redis) under automated scale conditions.
  • SaaS Security & Architecture: Background validating multi-tenant B2B SaaS applications where strict data isolation, high availability, and security compliance verification tools (like GitLab Ultimate, Sonarqube and Wiz) are paramount.
  • Reporting and Presenting: Experience building or maintaining lightweight reporting/dashboards that surface test coverage (automated vs. manual) across teams.

The anticipated on-target earnings range for the role is $90,000 -118,000 per year + equity + benefits. Actual salaries may vary and will be based on factors, such as the candidate's qualifications, skills, competencies, and proficiency for the role. Internal candidates who have current pay within or above the hiring range are still encouraged to apply if interested.
At LogicGate, our people are the foundation of everything we do. We are committed to delivering an exceptional experience for our employees and our customers by empowering and enabling our people to take ownership, make an impact, and deliver their best work.
Total Rewards
We are proud to offer a variety of competitive, inclusive, and comprehensive total rewards that are designed to support the unique needs of our employees both inside and outside of the workplace.
In addition to offering competitive salary and variable compensation plans, equity options, and flexible health and wellness benefits, we are proud to offer generous PTO, Annual Company Holidays, Health Days, and Summer Fridays.
Employees' growth and development are supported throughout their career journey through informal and formal programs and activities, including access to LinkedIn Learning, regular People Leader training, and our internal Mentorship Program.
Our Culture
At LogicGate, our culture and employee experience are grounded in our core values of Be as One, Do the Right Thing, Embrace Curiosity, Own It, Empower Customers, and Raise the Bar, which guide how we show up - for each other, our customers, and all we interact with.
We believe that the strongest teams are made up of individuals who bring their different identities, experiences, and perspectives to the table. We are committed to fostering an inclusive work environment where all employees' differences are celebrated and everyone is encouraged to bring their authentic selves to work.
We encourage everyone to join one of our Employee Resource Groups (AAPI @ LogicGate, Pride at LogicGate, and Women in LogicGate) to participate in and contribute to conversations that foster an inclusive culture.
LogicGate also believes strongly in giving back to the communities in which we live and work. To enable our teams to give back, we offer paid volunteer hours and company-wide charitable activities supporting a variety of organizations and causes.
We are proud to have been recognized as a top workplace by Built In, Crain's Chicago Business, the Chicago Tribune, and more. Visit our website to learn about our latest recognition.
Learn more about our culture here.