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Generative Ai Testing Jobs in Florida (NOW HIRING)

... generative AI, agentic AI, and decision-science problem statements. * Perform exploratory data analysis, statistical analysis, hypothesis testing, experimental design, feature engineering, predictive ...

New

Maintain AI system performance through regular updates, testing, optimization, and maintenance ... Strong understanding of generative AI, machine learning, automation, and large language models.

... Generative AI applications. * Participate in Agile ceremonies including Sprint Planning, Daily Standups, Reviews, and Retrospectives. Required Skills * Automation Testing using Java & Selenium

... Generative AI applications. * Participate in Agile ceremonies including Sprint Planning, Daily Standups, Reviews, and Retrospectives. Required Skills * Automation Testing using Java & Selenium

Showing results 41-60

Generative Ai Testing information

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. Certifications in AI or data science can enhance your qualifications and improve job prospects.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development that involves evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, making it a promising career path with increasing demand as AI technologies expand. Professionals in this area can find opportunities in tech companies, research labs, and startups focused on AI innovation.

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 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 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 popular job titles related to Generative Ai Testing jobs in Florida?

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

What job categories do people searching Generative Ai Testing jobs in Florida look for?

The top searched job categories for Generative Ai Testing jobs in Florida are:

What cities in Florida are hiring for Generative Ai Testing jobs?

Cities in Florida with the most Generative Ai Testing job openings:

Infographic showing various Generative Ai Testing job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 10% Part Time, 4% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Cyber AI Governance and Privacy Senior Consultant

Deloitte

Miami, FL

Full-time

Re-posted 18 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Designing and implementing AI governance operating models, intake workflows, risk tiering, approvals, documentation standards, exception handling, and audit-ready evidence processes for generative AI and agentic AI deployments.
  • Building and maintaining inventories for models, agents, tools, data sources, and integrations, with defined ownership, intended use, risk classification, and change-control requirements.
  • Conducting risk assessments across privacy, security, model risk, and misuse scenarios, including prompt injection, sensitive data exposure, excessive agency, and overreliance, and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions, including human-in-the-loop patterns, tool access controls, retrieval and grounding practices, logging, monitoring, token and data minimization, and incident response playbooks.
  • Integrating governance checkpoints into product and engineering delivery through architecture reviews, release gates, evaluation requirements, documentation automation, evidence capture, dashboards, and cross-functional collaboration with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science teams.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Experience translating policies and regulatory expectations into operational workflows and artifacts, including intake processes, inventories, decision logs, risk registers, responsibility assignment matrices, playbooks, privacy impact assessments, and data protection impact assessments.
  • Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and defining mitigations for privacy, security, model risk, and misuse.
  • Experience prototyping or automating governance workflows using Python or Structured Query Language and working with continuous integration and continuous deployment pipelines and cloud deployment basics.
  • Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience operationalizing AI governance aligned to the National Institute of Standards and Technology AI Risk Management Framework or ISO/IEC 42001.
  • Experience with generative AI safety and evaluation practices, including prompt injection testing, jailbreak resilience, hallucination measurement, toxicity scoring, harm scoring, and grounding effectiveness.
  • Experience with governance, workflow, or ticketing platforms, including OneTrust and governance, risk, and compliance systems, and integrating those platforms into engineering delivery processes.
  • Certifications such as Certified Information Privacy Professional/United States, Certified Information Privacy Manager, International Association of Privacy Professionals AI Governance Professional, Certified Information Security Manager, or Certified Information Systems Security Professional.
  • Experience in cyber or enterprise security environments, including data security, identity, audit logging, secure software development lifecycle practices, human-in-the-loop escalation pathways, exception handling, and automated safety protocols for autonomous systems.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Qualifications:

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Designing and implementing AI governance operating models, intake workflows, risk tiering, approvals, documentation standards, exception handling, and audit-ready evidence processes for generative AI and agentic AI deployments.
  • Building and maintaining inventories for models, agents, tools, data sources, and integrations, with defined ownership, intended use, risk classification, and change-control requirements.
  • Conducting risk assessments across privacy, security, model risk, and misuse scenarios, including prompt injection, sensitive data exposure, excessive agency, and overreliance, and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions, including human-in-the-loop patterns, tool access controls, retrieval and grounding practices, logging, monitoring, token and data minimization, and incident response playbooks.
  • Integrating governance checkpoints into product and engineering delivery through architecture reviews, release gates, evaluation requirements, documentation automation, evidence capture, dashboards, and cross-functional collaboration with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science teams.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Experience translating policies and regulatory expectations into operational workflows and artifacts, including intake processes, inventories, decision logs, risk registers, responsibility assignment matrices, playbooks, privacy impact assessments, and data protection impact assessments.
  • Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and defining mitigations for privacy, security, model risk, and misuse.
  • Experience prototyping or automating governance workflows using Python or Structured Query Language and working with continuous integration and continuous deployment pipelines and cloud deployment basics.
  • Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience operationalizing AI governance aligned to the National Institute of Standards and Technology AI Risk Management Framework or ISO/IEC 42001.
  • Experience with generative AI safety and evaluation practices, including prompt injection testing, jailbreak resilience, hallucination measurement, toxicity scoring, harm scoring, and grounding effectiveness.
  • Experience with governance, workflow, or ticketing platforms, including OneTrust and governance, risk, and compliance systems, and integrating those platforms into engineering delivery processes.
  • Certifications such as Certified Information Privacy Professional/United States, Certified Information Privacy Manager, International Association of Privacy Professionals AI Governance Professional, Certified Information Security Manager, or Certified Information Systems Security Professional.
  • Experience in cyber or enterprise security environments, including data security, identity, audit logging, secure software development lifecycle practices, human-in-the-loop escalation pathways, exception handling, and automated safety protocols for autonomous systems.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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