1

Ai Rmf Jobs in Arizona (NOW HIRING)

Job Summary : Empower AI is an organization focused on providing AI solutions for government ... RMF) leadership, including ATO sustainment, security assessments, POA&M development and management ...

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

New

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

New

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

New

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

New

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

New

... RMF, data protection, and Responsible AI policies - Supports system accreditation, documentation, testing, and evaluation activities - Collaborates with Government and contractor teams across ...

New

next page

Showing results 1-20

Ai Rmf information

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

To thrive as an AI RMF Specialist, you need expertise in risk management, AI/ML systems, compliance, and typically a background in computer science, data science, or cybersecurity. Familiarity with NIST AI RMF, model governance tools, and regulatory compliance platforms is essential, and certifications like CISSP or CISM are often advantageous. Strong analytical thinking, communication, and stakeholder management skills help navigate complex technical and ethical considerations. These abilities are crucial to ensure organizations deploy AI responsibly, mitigate risks, and meet legal and ethical standards.

What are some common challenges faced by professionals working in AI Risk Management Framework (RMF) roles?

Professionals in AI RMF roles often encounter challenges such as keeping up with rapidly evolving regulatory requirements and ensuring that AI systems remain compliant throughout their lifecycle. Another common challenge is collaborating effectively with cross-functional teams—including data scientists, legal, and IT security—to identify and mitigate risks associated with AI models. Additionally, balancing the need for innovative AI solutions with responsible risk management can be complex, requiring strong communication and critical thinking skills.

What are AI RMF professionals?

AI RMF professionals are experts who specialize in implementing and managing the Artificial Intelligence Risk Management Framework (AI RMF). This framework, developed by NIST, provides structured guidance for organizations to identify, assess, and mitigate risks associated with artificial intelligence systems. AI RMF professionals help ensure that AI technologies are trustworthy, ethical, and comply with relevant standards and regulations. Their work involves risk assessment, policy development, and collaboration with technical and compliance teams to integrate responsible AI practices.

What is the difference between Ai Rmf vs Ai Rmp?

AspectAi RmfAi Rmp
CertificationsRegistered Medical Fitness (RMF) certificationRegistered Medical Practitioner (RMP) license
Work EnvironmentMedical clinics, health screening centersHospitals, clinics, private practices
Industry UsageHealth screening, medical assessmentsMedical diagnosis, treatment
Common Search IntentRoles in medical fitness assessmentsMedical diagnosis and patient care

Ai Rmf and Ai Rmp are related healthcare roles but differ mainly in certification and scope. Ai Rmf focuses on medical fitness assessments, often in health screening centers, while Ai Rmp involves broader medical diagnosis and patient treatment. Understanding these differences helps in choosing the right career path or job role in the healthcare industry.

What are popular job titles related to Ai Rmf jobs in Arizona? For Ai Rmf jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Ai Rmf jobs? Cities in Arizona with the most Ai Rmf job openings:
Cyber AI Governance and Privacy Senior Consultant

Cyber AI Governance and Privacy Senior Consultant

Deloitte

Gilbert, AZ • On-site

Other

Posted 17 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 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 6/5/2026.

Work You'll Do

You will lead and deliver AI governance, privacy, and security outcomes across the AI lifecycle, including:

  • Designing pragmatic AI governance operating models (intake, risk tiering, approvals, documentation standards, exception handling, and audit readiness) with a focus on GenAI and agentic AI deployments.
  • Building and maintaining AI system inventories (models, agents, tools, data sources, integrations), with clear ownership, intended use, risk classification, and change-control expectations.
  • Conducting AI risk assessments for privacy, security, model risk, and misuse-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: human-in-the-loop patterns, tool access controls, safe retrieval and grounding practices, logging/monitoring, token and data minimization, and incident response playbooks.
  • Implementing "governance in the workflow" by integrating governance checkpoints into product and engineering delivery (architecture reviews, release gates, evaluation requirements, documentation automation, and evidence capture).
  • Standing up or enhancing evaluation and monitoring approaches for GenAI systems: test plans, safety and quality metrics, red teaming workflows, and reporting dashboards for leaders and risk stakeholders.
  • Partnering cross-functionally with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science to drive adoption and ensure governance guidance is usable, measurable, and repeatable.

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 one or more of the following: AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Demonstrated experience translating policies and regulatory expectations into operational workflows, artifacts, and controls (e.g., intake processes, inventories, decision logs, risk registers, RACI, playbooks).
  • Working knowledge of AI/ML/LLM systems and delivery lifecycles sufficient to assess real deployment risks and mitigations (training vs. RAG vs. fine-tuning vs. tool use, data dependencies, integration patterns).
  • Software development fluency: ability to collaborate with engineering teams on implementation details; ability to prototype or automate governance workflows in Python/SQL and to understand CI/CD and cloud deployment basics.
  • Practical experience with privacy program execution and artifacts (PIAs/DPIAs, vendor reviews, data inventories, data minimization, retention, and access control principles).
  • Ability to communicate clearly with both technical and non-technical stakeholders and produce executive-ready reporting.
  • Ability to travel 0-50%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available.

Preferred

  • Previous consulting or Big 4 experience.
  • Hands-on experience operationalizing AI governance aligned to frameworks such as the NIST AI RMF and/or ISO/IEC 42001, with awareness of risk-based AI regulatory regimes (e.g., EU AI Act).
  • Experience with GenAI safety and evaluation practices (prompt injection testing, jailbreak resilience, hallucination measurement, toxicity/harm scoring, grounding effectiveness).
  • Familiarity with governance tooling and workflow platforms (e.g., OneTrust, GRC platforms, ticketing/workflow systems) and how to integrate them into engineering delivery.
  • Certifications such as CIPP/US, CIPM, IAPP AIGP, CISM, or CISSP.
  • Prior experience in cyber or enterprise security contexts (data security, identity, audit logging, secure SDLC).
  • Experience designing Human-in-the-Loop escalation pathways, exception handling, and automated safety protocols for highly 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 $118,700 - 218,600. 

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 6/5/2026.

Work You'll Do

You will lead and deliver AI governance, privacy, and security outcomes across the AI lifecycle, including:

  • Designing pragmatic AI governance operating models (intake, risk tiering, approvals, documentation standards, exception handling, and audit readiness) with a focus on GenAI and agentic AI deployments.
  • Building and maintaining AI system inventories (models, agents, tools, data sources, integrations), with clear ownership, intended use, risk classification, and change-control expectations.
  • Conducting AI risk assessments for privacy, security, model risk, and misuse-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: human-in-the-loop patterns, tool access controls, safe retrieval and grounding practices, logging/monitoring, token and data minimization, and incident response playbooks.
  • Implementing "governance in the workflow" by integrating governance checkpoints into product and engineering delivery (architecture reviews, release gates, evaluation requirements, documentation automation, and evidence capture).
  • Standing up or enhancing evaluation and monitoring approaches for GenAI systems: test plans, safety and quality metrics, red teaming workflows, and reporting dashboards for leaders and risk stakeholders.
  • Partnering cross-functionally with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science to drive adoption and ensure governance guidance is usable, measurable, and repeatable.

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 one or more of the following: AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Demonstrated experience translating policies and regulatory expectations into operational workflows, artifacts, and controls (e.g., intake processes, inventories, decision logs, risk registers, RACI, playbooks).
  • Working knowledge of AI/ML/LLM systems and delivery lifecycles sufficient to assess real deployment risks and mitigations (training vs. RAG vs. fine-tuning vs. tool use, data dependencies, integration patterns).
  • Software development fluency: ability to collaborate with engineering teams on implementation details; ability to prototype or automate governance workflows in Python/SQL and to understand CI/CD and cloud deployment basics.
  • Practical experience with privacy program execution and artifacts (PIAs/DPIAs, vendor reviews, data inventories, data minimization, retention, and access control principles).
  • Ability to communicate clearly with both technical and non-technical stakeholders and produce executive-ready reporting.
  • Ability to travel 0-50%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available.

Preferred

  • Previous consulting or Big 4 experience.
  • Hands-on experience operationalizing AI governance aligned to frameworks such as the NIST AI RMF and/or ISO/IEC 42001, with awareness of risk-based AI regulatory regimes (e.g., EU AI Act).
  • Experience with GenAI safety and evaluation practices (prompt injection testing, jailbreak resilience, hallucination measurement, toxicity/harm scoring, grounding effectiveness).
  • Familiarity with governance tooling and workflow platforms (e.g., OneTrust, GRC platforms, ticketing/workflow systems) and how to integrate them into engineering delivery.
  • Certifications such as CIPP/US, CIPM, IAPP AIGP, CISM, or CISSP.
  • Prior experience in cyber or enterprise security contexts (data security, identity, audit logging, secure SDLC).
  • Experience designing Human-in-the-Loop escalation pathways, exception handling, and automated safety protocols for highly 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 $118,700 - 218,600. 

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:

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom