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Ai Risk Jobs in Utah (NOW HIRING)

EnerSys

VP Enterprise AI Enablement

Salt Lake City, UT · On-site

$275K - $315K/yr

Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management in partnership with Legal, Cybersecurity, IT Architecture, HR, and Compliance. Own AI investment ...

NRG

Senior AI Security Engineer

UT · On-site

$107K - $147K/yr

Develop and maintain dashboards to report key cybersecurity metrics and risk indicators * Automate ... Hands-on experience with AI systems, including building or working with AI agents, LLM-based ...

Pwc

RFM AI Governance Manager

Salt Lake City, UT · On-site

$73K - $244K/yr

Responsibilities - Develop and implement AI governance frameworks - Conduct risk assessments to maintain compliance with firm policies - Guide the adaptation of AI usage and maintenance protocols ...

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Ai Risk information

What is the difference between Ai Risk vs Data Scientist?

AspectAi RiskData Scientist
Required CredentialsBackground in AI, risk management, certifications in AI safetyDegree in Computer Science, Statistics, or related fields; certifications in data analysis
Work EnvironmentRisk assessment teams, AI development projects, regulatory settingsData analysis teams, research labs, tech companies
Employer & Industry UsageTech firms, AI safety organizations, regulatory agenciesTech companies, finance, healthcare, research institutions
Common Search & Comparison IntentUnderstanding AI risk roles, career differencesData analysis careers, AI safety roles

Ai Risk professionals focus on identifying and mitigating risks associated with artificial intelligence systems, often working in safety, ethics, and regulatory contexts. Data Scientists analyze large datasets to extract insights, build models, and support decision-making across various industries. While both roles require technical skills, Ai Risk emphasizes safety and ethical considerations, whereas Data Scientists focus on data analysis and modeling.

What are the most commonly searched types of Ai Risk jobs in Utah? The most popular types of Ai Risk jobs in Utah are:
What are popular job titles related to Ai Risk jobs in Utah? For Ai Risk jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Ai Risk jobs in Utah look for? The top searched job categories for Ai Risk jobs in Utah are:
What cities in Utah are hiring for Ai Risk jobs? Cities in Utah with the most Ai Risk job openings:
Ai Risk jobs near you
Infographic showing various Ai Risk job openings in Utah as of June 2026, with employment types broken down into 100% Full Time. Highlights an 83% In-person, and 17% Remote job distribution.

AI Research Fellow / Senior AI Policy Researcher

Utah Division of Human Resource Management

Salt Lake City, UT

Other

Posted 9 days ago

Job description

Duties will include, but are not limited to, the following:

  • Independently scope and execute research projects on emerging AI policy questions, including defining the question, identifying relevant technical and empirical evidence, interviewing experts, evaluating tradeoffs, and producing written recommendations for policymakers and regulators.
  • Research technical aspects, capabilities, limitations, and societal impacts of AI technologies in support of the AI Learning Lab's policy agenda.
  • Evaluate evidence and forecasts concerning the impact of human-AI interactions on health, economic activity, education, consumer welfare, and public institutions.
  • Draft executive policy memos, legislative briefings, technical explainers, risk assessments, regulatory mitigation analyses, and recommendations for agency and legislative decision-makers.
  • Interface with business leaders, technologists, researchers, regulators, legislators, and lawyers to understand AI applications and help stakeholders develop well-reasoned regulatory responses.
  • Advise on the development of regulatory and legal standards as the Office's recommendations move through agency, legislative, and stakeholder processes.
  • Work with experts across disciplines to understand the benefits, risks, evidence gaps, and practical constraints associated with AI deployment in Utah.

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