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Ai Risk Management Framework Jobs (NOW HIRING)

NC SECU

Model Risk Governance Manager

Raleigh, NC · Hybrid

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 ...

Lincoln Financial

Analyst, AI Risk Management

Radnor, PA · Hybrid

$72K - $131K/yr

Requisition #: 76178 The Role at a Glance This position is responsible for executing AI Risk Management practices across the enterprise by identifying, assessing, mitigating, and monitoring complex ...

AMA CONSULTING LLC.

AI Governance Lead

Lanham, MD · On-site

This role will ensure alignment with federal AI policy, ethical AI standards, and risk management frameworks. This position plays a critical role in helping organizations deploy AI responsibly ...

Lincoln Financial

Analyst, AI Risk Management

Radnor, PA · On-site

$72K - $131K/yr

Requisition #: 76178 The Role at a Glance This position is responsible for executing AI Risk Management practices across the enterprise by identifying, assessing, mitigating, and monitoring complex ...

Lincoln Financial

Analyst, AI Risk Management

Radnor, PA · Hybrid

$72K - $131K/yr

Requisition #: 76178 The Role at a Glance This position is responsible for executing AI Risk Management practices across the enterprise by identifying, assessing, mitigating, and monitoring complex ...

kgs

Risk Management Framework SME

Fort Belvoir, VA · On-site

Tuknik Government Services, LLC a Koniag Government Services company , is seeking a Risk Management Framework SME with a TS/SCI security clearance to support TGS and our government customer at Fort ...

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How much do ai risk management framework jobs pay per hour?

As of Jun 30, 2026, the average hourly pay for ai risk management framework in the United States is $30.34, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $38.70 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Risk Management Framework Specialist, and why are they important?

To thrive as an AI Risk Management Framework Specialist, you need expertise in risk assessment, AI/ML systems, and regulatory compliance, typically supported by a degree in computer science, data science, or a related field. Familiarity with frameworks like NIST AI RMF, risk management tools, and governance platforms is often required, as well as relevant certifications such as CRISC or CISSP. Strong analytical thinking, attention to detail, and clear communication skills help professionals navigate complex technical and ethical challenges. These skills ensure the safe, ethical, and compliant deployment of AI systems within organizations.

What are some common challenges encountered when implementing an AI Risk Management Framework in an organization?

Implementing an AI Risk Management Framework often involves navigating challenges such as aligning diverse stakeholder expectations, integrating risk assessments into existing workflows, and ensuring compliance with rapidly evolving regulations. Team members may need to bridge knowledge gaps between technical AI development and risk management practices, which requires effective communication and training. Additionally, organizations must continuously update their frameworks to address new AI risks, making adaptability and ongoing learning essential for success in this role.

What is the difference between Ai Risk Management Framework vs Data Scientist?

AspectAi Risk Management FrameworkData Scientist
Primary FocusIdentifying and mitigating AI-related risks, ensuring ethical and safe AI deploymentAnalyzing data to extract insights, build models, and support decision-making
Required CredentialsKnowledge of AI ethics, risk assessment, and relevant certificationsDegree in data science, statistics, or related fields; programming skills
Work EnvironmentCorporate, tech companies, industries deploying AI systemsResearch labs, tech firms, finance, healthcare

The Ai Risk Management Framework focuses on managing risks associated with AI systems, ensuring safety and compliance. In contrast, Data Scientists primarily analyze data to develop models and generate insights. While both roles require technical skills, their core objectives differ: risk mitigation versus data analysis.

What is an AI Risk Management Framework?

An AI Risk Management Framework is a structured approach for identifying, assessing, and mitigating risks associated with the design, development, deployment, and use of artificial intelligence systems. It provides guidelines and best practices to ensure AI systems are trustworthy, ethical, and aligned with legal and societal expectations. Organizations use these frameworks to address potential challenges such as bias, security vulnerabilities, privacy concerns, and unintended consequences. By implementing an AI risk management framework, companies can better manage risks and improve transparency and accountability in their AI initiatives.
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Ai Risk Management Framework jobs near you

Model Risk Governance Manager

NC SECU

Raleigh, NC • Hybrid

Full-time

Posted 17 days ago

Key responsibilities

  • Develop and execute policies, standards, and internal procedures for all phases of the model and AI life cycle.

  • Own the model risk management framework and report on model governance, development, validation, and monitoring for the organization.

  • Design and maintain AI governance frameworks, standards, and research to guide responsible AI adoption and ensure safe, ethical, and regulatory-aligned AI practices.

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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