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Generative Ai Testing Jobs in Bolingbrook, IL (NOW HIRING)

Crowe LLP

AI Project Coordinator

Chicago, IL · On-site

Working knowledge of generative AI tools (ChatGPT, Claude, Copilot) and ability to apply them to ... Proficiency with data manipulation, cleaning, and structuring to support AI testing and solution ...

Crowe LLP

AI Project Coordinator

Chicago, IL · On-site

Working knowledge of generative AI tools (ChatGPT, Claude, Copilot) and ability to apply them to ... Proficiency with data manipulation, cleaning, and structuring to support AI testing and solution ...

Crowe Advisory LLC

AI Project Coordinator

Chicago, IL · On-site

$62 - $100/hr

Working knowledge of generative AI tools (ChatGPT, Claude, Copilot) and ability to apply them to ... Proficiency with data manipulation, cleaning, and structuring to support AI testing and solution ...

Tekfortune Inc.

AI Solution Architect

Chicago, IL · On-site

$65 - $85.50/hr

Generative AI Other skills: AWS, Machine Learning, Cloud & Data Engineering Years Of Experience: 11 ... CI/CD pipelines for automated testing of non-deterministic AI outputs. Observability & Responsible ...

RPA Infotech Digital Inc.

AI Solution Architect

Chicago, IL · On-site

$65 - $85.50/hr

Generative ai, AWS, Machine Learning, Cloud & Data Engineering Role Summary & Objectives • ... testing of non-deterministic AI outputs. Observability & Responsible AI • Observability and ...

RPA Infotech Digital Inc.

AI Solution Architect

Chicago, IL · On-site

$65 - $85.50/hr

Generative ai Other skills: AWS, Machine Learning, Cloud & Data Engineering Role Summary ... testing of non-deterministic AI outputs. Observability & Responsible AI • Observability and ...

Deloitte

Lead Generative AI Data Engineer III

Chicago, IL · On-site

$105K - $139K/yr

Lead the design, development, testing, and deployment of machine learning and artificial ... Manage AI engineering workstreams by assigning work, reviewing deliverables, and driving quality ...

Jobtailor

AI Specialist - Operations Intern

Niles, IL · On-site

$60 - $84/hr

* Assist in researching, evaluating, and testing AI technologies and tools * Support the ... Basic understanding of Artificial Intelligence, Machine Learning, or Generative AI concepts

New

Neura Market

AI deployment engineer (Central)

Chicago, IL · On-site

$150 - $210/hr

... generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin ... Early-detection cancer testing through Galleri * Flexible spending account and dependent FSA ...

Writer

AI deployment engineer (Central)

Chicago, IL · On-site

$131K - $166K/yr

... generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin ... Early-detection cancer testing through Galleri * Flexible spending account and dependent FSA ...

WRITER

AI deployment engineer (Central)

Chicago, IL · On-site

$90 - $130/hr

... generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago ... Early‑detection cancer testing through Galleri * Flexible spending account and dependent FSA ...

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All JobsGenerative Ai Testing JobsGenerative Ai Testing Jobs in Bolingbrook, IL

Generative Ai Testing information

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$31

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$75

How much do generative ai testing jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for generative ai testing in Bolingbrook, IL is $53.13, according to ZipRecruiter salary data. Most workers in this role earn between $43.75 and $60.87 per hour, depending on experience, location, and employer.

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 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 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 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 do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in Bolingbrook, IL?

For Generative Ai Testing jobs in Bolingbrook, IL, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Bolingbrook, IL look for?

The top searched job categories for Generative Ai Testing jobs in Bolingbrook, IL are:

What cities near Bolingbrook, IL are hiring for Generative Ai Testing jobs?

Cities near Bolingbrook, IL with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you

Lead Engineer (Generative AI)

Amtex Enterprises Inc

Chicago, IL • On-site

$150 - $190/hr

Other

Posted 17 days ago

Job description

Job Title : Lead Engineer (Generative AI)

Duration: 6-12 plus months

Location
  • Minneapolis/St. Paul “Twin Cities,” MN
  • Bay Area, CA – San Francisco and surrounding areas
  • Charlotte, NC
  • Chicago, IL
Job Description

Job Summary

The Lead Engineer (Generative AI) is a senior technical role responsible for designing, developing, and operationalizing enterprise-scale Generative AI (GenAI) solutions. This position combines deep hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI architectures with strong technical leadership to deliver secure, scalable, and resilient AI systems.

The role partners across engineering, product, and business teams to translate complex requirements into production-ready AI capabilities aligned with enterprise standards for security, risk, and responsible AI.

Key Responsibilities
  1. GenAI Solution Engineering
    • Design, develop, and deploy GenAI solutions leveraging:
      • Large Language Models (LLMs)
      • Retrieval-Augmented Generation (RAG) architectures
      • Prompt engineering techniques
      • Agentic AI workflows and orchestration
    • Build intelligent systems using frameworks such as LangChain, LangGraph, AWS Bedrock, and Microsoft Foundry Agent Service
    • Evaluate emerging tools and frameworks to continuously improve solution quality and innovation
  2. GenAIOps & Lifecycle Management
    • Lead the end-to-end lifecycle of GenAI solutions, including:
      • Solution architecture and engineering
      • Integration with enterprise systems
      • Secure deployment and release management
      • Monitoring, observability, and continuous optimization
    • Implement GenAIOps best practices to ensure scalability, reliability, and cost efficiency
    • Establish logging, evaluation, and feedback mechanisms for production AI systems
  3. Cloud, Platform & Scalability Engineering
    • Architect and deploy GenAI applications across cloud environments (Azure and AWS)
    • Design distributed systems capable of supporting high-throughput, low-latency AI workloads
    • Leverage modern infrastructure practices:
      • Containerization (Docker)
      • Orchestration (Kubernetes)
      • Infrastructure as Code (Terraform, ARM/Bicep)
    • Ensure high availability, performance, and enterprise-grade security
  4. Software Engineering & Architecture
    • Develop scalable, maintainable applications using Python and microservices-based architectures
    • Apply secure coding standards and robust data handling practices for regulated environments
    • Build and manage CI/CD pipelines supporting automated testing, deployment, and release management
    • Enforce engineering best practices including code reviews, testing, and documentation
  5. Technical Leadership & Influence
    • Provide architectural leadership and guidance across GenAI initiatives
    • Drive critical design decisions for large-scale, complex AI solutions
    • Mentor and coach senior engineers and development teams
    • Translate business requirements into scalable, secure, and resilient technical solutions
    • Partner with stakeholders across product, business, risk, and security functions
Basic Qualifications
  • Bachelor’s degree, or equivalent work experience
  • Six to eight years of relevant experience
Experience Should Include
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • 8+ years of experience in software engineering, platform engineering, or AI/ML solutions
  • 2+ years hands-on experience with GenAI technologies, including LLMs and RAG architectures and vector databases
  • Strong knowledge of agentic AI concepts and frameworks (e.g., LangChain, LangGraph)
  • Experience with cloud platforms (Azure and/or AWS)
  • Deep understanding of distributed systems and scalable architecture patterns
  • Proficiency in Python and microservices-based development
  • Experience with Docker, Kubernetes, and Infrastructure as Code tools
  • Demonstrated technical leadership and mentoring experience
Preferred Qualifications
  • Experience implementing GenAI solutions in enterprise or regulated environments
  • Familiarity with observability frameworks and AI lifecycle tooling
  • Understanding of AI governance, security, and compliance requirements
  • Experience contributing to or working with AI/ML or GenAI frameworks
  • Background in financial services or other highly regulated industries
Core Competencies Technical Depth & Innovation
  • Strong expertise in GenAI architectures and evolving AI technologies
  • Ability to balance experimentation with enterprise-grade reliability
Architecture & Systems Thinking
  • Designs scalable, distributed, and resilient systems
  • Aligns architecture decisions with enterprise standards and long-term strategy
Execution & Operational Excellence
  • Drives end-to-end delivery from concept through production
  • Ensures high standards for quality, security, and performance
Leadership & Collaboration
  • Influences without authority and leads through technical expertise
  • Mentors engineers and elevates overall team capability
Business & Stakeholder Alignment
  • Translates complex technical concepts into business outcomes
  • Partners effectively across product, engineering, and leadership teams
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