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

AI deployment engineer (Central)

Chicago, IL ยท 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 ...

AI deployment engineer (Central)

Chicago, IL ยท 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 ...

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

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for generative ai testing in Deerfield, IL is $54.64, according to ZipRecruiter salary data. Most workers in this role earn between $45.00 and $62.60 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 job categories do people searching Generative Ai Testing jobs in Deerfield, IL look for?

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

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

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

AI Business Engineer - Investment Banking Experience

Raymondjames

Chicago, IL โ€ข Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago


Job description

Job Description Summary

The AI Business Engineer supports the adoption and effective use of generative AI across the Investment Bank and Capital Markets & Advisory functions by designing, building, and improving AI-powered solutions across banker workflows through custom GPTs and prompts and emerging agent-based tools. This role blends technical curiosity with practical application and deep business knowledge, contributing to prompt engineering, solution development, and user support while maintaining best practices and documentation. The individual partners with stakeholders to deliver training, troubleshoot issues, and enhance user experience, while also evaluating technology trends and vendors to drive innovation and business value.

Job Description

Responsibilities

  • This role will directly support the Investment Bank and Capital Markets & Advisory function and its use of generative AI, including GPTs and future agent-based solutions.
  • Support the design, development, testing, and ongoing improvement of GPTs, AI-powered workflows, and (over time) agent-based solutions
  • Assist with prompt engineering, prompt optimization, and documentation of effective prompting patterns and use cases
  • Help maintain standards, best practices, and internal documentation related to AI tools, automation, and innovation platforms
  • Provide hands-on support to internal users, helping troubleshoot issues and improve overall user experience with AI-enabled tools
  • Design and deliver role-specific training to finance professionals
  • Contribute to short- and long-term innovation roadmaps through research, analysis, and execution support
  • Analyze technology trends, tools, and vendor offerings to identify opportunities for experimentation or business value
  • Generate insights and recommendations that help improve internal technology offerings and identify areas for growth
  • Assist with data analysis and reporting related to innovation initiatives, pilots, and outcomes
  • Create and maintain presentation materials, including PowerPoint decks, charts, and visuals for leadership and stakeholder updates
  • Facilitate meetings with internal teams and external vendors; capture notes, actions, and follow-ups
  • Draft concise summaries, reports, or briefing materials on technology topics, vendors, or pilot results
  • Contribute ideas and perspectives to brainstorming sessions and innovation ideation efforts

Skills

  • The ideal candidate is curious, technically inclined, and excited about applying emerging technologies-especially generative AI-to real business problems.
  • 1-4 years of experience in technology, software, digital innovation, or related roles (financial services experience a plus, but not required)
  • Strong interest in generative AI, automation, and modern software platforms (e.g., LLMs, GPTs, agents, APIs, low-code/no-code tools)
  • Working knowledge of Python and SQL to support data exploration, workflow automation, and AI prototype development; ability to read, modify, and apply scripts with guidance from engineering partners - deep software engineering experience not required
  • Proficiency in data analysis using advanced Excel (e.g., pivot tables, XLOOKUP/VLOOKUP, conditional logic) to support reporting, pilot measurement, and business case development
  • Experience supporting or managing vendors, including coordination around licenses, contracts, or service delivery
  • Working knowledge of project and program management fundamentals
  • Ability to operate effectively in a fast-paced, evolving environment and adapt quickly as priorities and technologies change
  • Demonstrated ability to think creatively and encourage new approaches or ways of working
  • Strong written communication skills, with the ability to explain technical or complex concepts clearly and concisely
  • Comfortable creating and interpreting charts, diagrams, tables, and other data visualizations
  • Genuine interest in following technology trends, innovation research, and emerging tools
  • Excellent verbal communication and collaboration skills
  • High attention to detail with the ability to manage multiple workstreams simultaneously
  • Team-oriented mindset with the ability to work across technical and non-technical stakeholders

What success looks like

  • High-value AI use cases are moved from idea to pilot to scaled adoption.
  • Solutions are deployed with clear testing, documentation, and governance controls.
  • Banker adoption increases and workflows show measurable improvement in speed, quality, or user experience.
  • The team develops reusable assets and a repeatable operating model rather than one-off prompts.

Education

Bachelor's degree in computer science, engineering, information systems, data science, finance, economics, or a related field, or equivalent practical experience.

Work Experience

General Experience - 1 to 6 years

Education

Bachelor's (Required)

Work Experience

General Experience - 3 to 6 years

Certifications

Salary Range

$65,000.00-$0.00

Travel

Workstyle

Hybrid

The total compensation for this position includes base salary or wages, and may include components such as additional compensation (cash or equity), discretionary bonuses, or commissions. This position is eligible for a benefits package that may include medical, dental, and vision; life insurance; critical illness insurance and accident insurance; disability benefits; retirement savings; paid time off (including vacation, holidays, and sick leave); and parental leave. Eligibility for benefits and specific offerings may vary based on position and employment status. To view more details of the benefits offered, visit Myrjbenefits.com.

At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
Grow professionally and inspire others to do the same
Work with and through others to achieve desired outcomes
Make prompt, pragmatic choices and act with the client in mind
Take ownership and hold themselves and others accountable for delivering results that matter
Contribute to the continuous evolution of the firm

At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.