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Ai Risk Manager Jobs in Raleigh, NC (NOW HIRING)

Ensure that AI capabilities are delivered safely, ethically, and in alignment with regulatory ... NIST AI Risk Management Framework, ISO 42001). * Programming skills in a statistical programming ...

Join our team and use advanced data, AI, and emerging technologies with industry insights to help ... Credit Risk, Liquidity Risk, Market Risk, Capital Management/Stress Testing * Knowledge of ...

AI Governance Analyst About the Role An AI Governance Analyst helps an organization build, monitor ... Support model risk management processes, including documentation, validation, and lifecycle ...

TAMs are accountable for translating Varonis capabilities into reduced risk, controlled access, and safe AI adoption across customer environments. To be a successful Technical Account Manager you ...

TAMs are accountable for translating Varonis capabilities into reduced risk, controlled access, and safe AI adoption across customer environments. To be a successful Technical Account Manager you ...

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Ai Risk Manager information

See Raleigh, NC salary details

$50.1K

$108.4K

$165.3K

How much do ai risk manager jobs pay per year?

As of Jun 22, 2026, the average yearly pay for ai risk manager in Raleigh, NC is $108,441.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,500.00 and $125,400.00 per year, depending on experience, location, and employer.

What is the difference between Ai Risk Manager vs Data Scientist?

AspectAi Risk ManagerData Scientist
Required CredentialsTypically requires a degree in risk management, AI, or related fields; certifications in AI or risk management are commonRequires a degree in computer science, statistics, or related fields; certifications in data analysis or machine learning are common
Work EnvironmentWorks in financial, insurance, or tech industries focusing on AI risk assessment and mitigationWorks across industries analyzing data, building models, and deriving insights
Employer & Industry UsageUsed by organizations managing AI deployment risks, especially in regulated sectorsUsed by companies developing AI solutions, data-driven products, and analytics teams

The main difference is that an Ai Risk Manager focuses on identifying and mitigating risks associated with AI systems, often requiring knowledge of risk management and AI ethics. In contrast, a Data Scientist primarily analyzes data and builds models to extract insights, with less emphasis on risk mitigation. Both roles may overlap in AI projects but serve distinct functions within organizations.

What are popular job titles related to Ai Risk Manager jobs in Raleigh, NC? For Ai Risk Manager jobs in Raleigh, NC, the most frequently searched job titles are:
What cities near Raleigh, NC are hiring for Ai Risk Manager jobs? Cities near Raleigh, NC with the most Ai Risk Manager job openings:

Model Risk Governance Manager

State Employees' Credit Union

Raleigh, NC • On-site

Full-time

Posted 10 days ago


State Employees' Credit Union (North Carolina) rating

8.2

Company rating: 8.2 out of 10

Based on 23 frontline employees who took The Breakroom Quiz


Job description

If you are motivated and believe in the credit union philosophy of "People Helping People," join our team!
Essential Responsibilities:
  • (30%) Development and execution of policies, standards, and internal procedures for all phases of the model and AI life cycle, including identification, risk assessment, definition of control objectives, ongoing monitoring, and retirement.
  • (20%) Ownership of the model risk management framework and reporting on model governance, development, validation, and monitoring for the organization. Responsible for creating and ongoing reporting of key risk indicators and management reporting for senior risk management stakeholders, management committees, and board-level committees.
  • (20%) Design and maintain AI governance frameworks, standards, and research to guide responsible AI adoption. Embed responsible, transparent, and controlled AI practices across the full AI life cycle, from design and development to deployment and monitoring. Ensure that AI capabilities are delivered safely, ethically, and in alignment with regulatory expectations, while enabling speed, scalability, and business value. Partner with technology, privacy, operational, and compliance risk leaders to ensure AI risk practices are well-integrated.
  • (10%) Manage and develop model risk and AI risk governance staff.
  • (10%) Ensure overall compliance of the program with regulatory guidance on model risk management and artificial intelligence, staying current with changes in regulatory expectations and leading industry practices.
  • (10%) Provide training and communication around the expectations of the MRM program and AI risk management to stakeholders across the organization.

Required Education & Experience (Knowledge, Skills, & Abilities):
  • Masters in a quantitative discipline (Economics, statistics, finance, data science or analytics, math, physics, or related field).
  • 5+ years of experience in modeling or analytics, including experience developing enterprise-wide policies, standards and protocols in model risk, AI, or a related discipline.
  • Ability to understand model conceptual design, testing of performance, controls over data flows, and compliance of model results with intended application.
  • Must possess a deep understanding of regulatory guidance and expectations in Model Risk Management (e.g., SR 26-2, SR 15-19) and Artificial Intelligence (e.g. NIST AI Risk Management Framework, ISO 42001).
  • Programming skills in a statistical programming language, such as SAS, R, or Python. Ability to independently write computer code to perform analysis on complex modeling and analytical challenges and to review code written by others for accuracy and efficiency.
  • Subject matter expertise in advanced mathematical and statistical modeling techniques, such as competing risk logistic regression, time series analysis, ordinary least squares, Monte Carlo simulation, and machine learning techniques (e.g. XGBoost).
  • Excellent oral and written communication skills. Experience writing and reviewing detailed technical validation reports and/or model development documentation.
  • Familiarity with modern artificial intelligence (AI), including large language models (LLMs), retrieval augmented generation, generative AI, agentic AI, and the approaches and architecture required to harness and manage the risks of these tools.
  • Strong attention to detail and the ability to independently formulate solutions to complex modeling and analytical challenges without existing procedures or precedent. Ability to mentor staff through complex analytical challenges and difficult technical conversations with internal and external stakeholders.
  • Ability to evaluate model risks, weigh pros and cons of risk mitigation, and communicate very technical concepts in plain language.
  • Perform job functions independently with limited day-to-day oversight from supervisor.

Preferred Education & Experience (Knowledge, Skills, & Abilities):
  • Experience managing teams of technical individual contributors and/or external vendors performing technical modeling work
  • Experience in financial services or consulting industry
  • Experience developing or validating models used for CECL, Credit Risk, CCAR/Stress Testing, PPNR, ALM, loan pricing and/or mortgage servicing rights, derivatives, Compliance (BSA/AML/OFAC), Liquidity, or Fraud
  • Subject matter expertise in generative large language models (Artificial Intelligence)
  • FRM or CFA certification

Job Environment & Physical Requirements:
  • Hybrid expectations
  • Sitting for prolonged periods
  • Computer for prolonged periods

SECU provides equal employment opportunity to all qualified persons regardless of race, color, religion, age, sex, sexual orientation, gender identity, national origin, genetic information, disability, veteran status, or other classification protected by law.
Disclaimer
State Employees' Credit Union reserves the right to fill this role at a higher/lower level based on business need.

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