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What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI executive, often requiring advanced skills, extensive experience, and sometimes leadership responsibilities. These roles are usually found in large tech companies or specialized AI firms and may include bonuses, stock options, or other incentives that contribute to the total compensation.

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 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 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.

Which 3 jobs will survive AI?

For an AI RMF (Risk Management Framework) specialist, jobs that involve complex decision-making, strategic planning, and human oversight are more likely to survive AI automation. These include roles such as cybersecurity analysts, compliance managers, and risk auditors, which require critical thinking, understanding of organizational context, and interpersonal skills that AI cannot fully replicate.

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 job makes $10,000 a month without a degree?

In the field of AI RMF (Risk Management Framework), high-paying roles such as AI project managers or senior data analysts can earn $10,000 or more monthly without a formal degree, provided they have strong technical skills, certifications, and experience. These roles often require expertise in AI tools, cybersecurity, or risk assessment, and may involve self-education or industry certifications instead of traditional degrees.

What is an AI RMF?

An AI RMF (Artificial Intelligence Risk Management Framework) is a structured approach used by AI professionals to identify, assess, and mitigate risks associated with AI systems. It involves implementing best practices, standards, and tools to ensure AI safety, reliability, and compliance throughout the development and deployment process.
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What job categories do people searching Ai Rmf jobs in Arizona look for? The top searched job categories for Ai Rmf jobs in Arizona are:
What cities in Arizona are hiring for Ai Rmf jobs? Cities in Arizona with the most Ai Rmf job openings:
Ai Rmf jobs near you

AI Security Architect

Futran Tech Solutions Pvt. Ltd.

Phoenix, AZ • On-site

$63.25 - $81.75/hr

Full-time

Posted 8 days ago

Job description

Hello,
Greetings for the day!
My name is Stella, and I am a Technical Recruiter at Futran Solutions. I am reaching out to you on an exciting job opportunity with one of our clients. Please let me know your interest and a good time to connect with you to take it forward.
Title: AI Security Architect
Location: Phoenix AZ - Onsite
Duration: Full Time / Contract
Role Summary The Security Architect will be part of a team whose role is to assure enterprise security architecture with a focus on the review and authorship of Architecture Decision Records (ADRs) and Security Architecture Review Board (SARB) submissions. The role blends deep technical acumen with emerging expertise in Generative AI (GenAI) and Agentic systems, ensuring secure design, governance, and responsible adoption of intelligent automation within the enterprise.
Key Responsibilities
Architecture Review & Advisory
Lead security reviews of solution and domain architectures, ADRs, and AI-enabled platforms.
Assess GenAI and agentic solution designs for model security, data protection, prompt integrity, provenance, and safe orchestration of agents.
Evaluate proposals for alignment with enterprise standards, regulatory expectations, and risk tolerance.
Produce actionable review comments with traceable recommendations, covering both traditional and AI-driven architectures.
Authoring & Governance
Author and maintain ADRs, patterns, and reference architectures-including those covering GenAI system integration, LLM usage, and multi-agent frameworks.
Ensure architectural documentation expresses the problem space, options, controls, and trade-offs clearly and defensibly.
Promote structured architectural reasoning supported by both human and GenAI-assisted analysis workflows.
GenAI & Agentic Security
Define and assess controls for GenAI systems, including:
Model access, data boundary, and prompt injection defenses.
Guardrails for AI agents performing autonomous actions or multi-step reasoning.
Secure orchestration, isolation, and human oversight mechanisms.
Evaluate the security of agent frameworks, LLM pipelines, and model-hosting platforms (e.g., Vertex AI, Azure OpenAI).
Contribute to enterprise policy for responsible AI use and GenAI-assisted development.
Technical Leadership
Provide domain expertise in application, cloud, and data security-augmented by AI security design considerations.
Support teams in safely embedding GenAI copilots, RAG systems, and autonomous agents within business processes.
Lead threat modeling for composite systems where GenAI interacts with APIs, data stores, and user environments.
Continuous Improvement & Automation
Use and refine GenAI tools for document review, security design assistance, and ADR quality assurance.
Develop reusable prompts, review heuristics, and decision frameworks that enhance SARB throughput and consistency.
Mentor peers in human-AI collaborative authoring, emphasizing accountability and verification of AI output.
Core Competencies
Enterprise security architecture (SABSA, TOGAF, NIST CSF).
GenAI systems architecture, LLM lifecycle, and model governance.
AI security patterns (threat modeling for LLMs, data leakage prevention, agent control).
Strong authorship and analytical writing-clear articulation of decisions and consequences.
Familiarity with tools for architectural diagramming, review automation, and GenAI-assisted design (e.g., Lang Chain, OpenAI GPT, Guardrails AI).
Broad experience across cloud, data, application, and API security domains.
Qualifications:
Bachelor's or Master's in Computer Science, Cybersecurity, or related field.
7+ years of experience in architecture or security design, including AI-related systems.
Desirable certifications: CISSP, CCSP, SABSA, TOGAF, or AI-specific credentials (e.g., NIST AI RMF, MIT AI Ethics, Azure AI Engineer).
Demonstrable experience with secure implementation of GenAI or autonomous agents in enterprise settings.
Success Measures
Secure-by-design adoption of GenAI and agentic capabilities across business domains.
Clear, complete, and AI-assisted ADRs produced and reviewed efficiently.
Reduced residual security risk in AI and non-AI solutions through proactive architectural engagement.
Recognition as a thought leader in secure GenAI architecture and governance.

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