ZipRecruiter

Log In

1

Ai Rmf Jobs in Grand Prairie, TX (NOW HIRING)

Celersoft

Security Architect

Dallas, TX · Hybrid

$90 - $100/hr

Practical application of MITRE ATLAS, OWASP for LLM Applications, and NIST AI RMF for threat modeling and control mapping. Purple Teaming & Adversary Emulation: Experience designing and testing ...

Celersoft

Security Architect

Dallas, TX · On-site

$120 - $160/hr

Practical application of MITRE ATLAS, OWASP for LLM Applications, and NIST AI RMF for threat modeling and control mapping. * Purple Teaming & Adversary Emulation: Experience designing and testing ...

Whitley Penn

AI Governance Senior Analyst

Plano, TX · On-site

$110 - $170/hr

Strong understanding of AI risk management frameworks (NIST AI RMF, OWASP Top 10 for Agentic Applications, ISO 42001) rather than normal risk frameworks. * Some knowledge of GLBA, SEC and FTC ...

Celersoft

Security Architect

Dallas, TX · Hybrid

$64.25 - $83/hr

Familiarity with NIST AI RMF , OWASP Top 10 for LLMs , and audit/compliance standards for autonomous AI operations. * Agile Delivery & Stakeholder Influence: Experience collaborating in cross ...

Whitley Penn

AI Governance Senior Analyst

Dallas, TX · Hybrid

$82K - $108K/yr

Strong understanding of AI risk management frameworks (NIST AI RMF, OWASP Top 10 for Agentic Applications, ISO 42001) rather than normal risk frameworks. * Some knowledge of GLBA, SEC and FTC ...

Whitley Penn

AI Governance Senior Analyst

Plano, TX · Hybrid

$82K - $108K/yr

Strong understanding of AI risk management frameworks (NIST AI RMF, OWASP Top 10 for Agentic Applications, ISO 42001) rather than normal risk frameworks. * Some knowledge of GLBA, SEC and FTC ...

Whitley Penn

AI Governance Senior Analyst

Plano, TX · On-site

$82K - $108K/yr

Strong understanding of AI risk management frameworks (NIST AI RMF, OWASP Top 10 for Agentic Applications, ISO 42001) rather than normal risk frameworks. * Some knowledge of GLBA, SEC and FTC ...

Kyndryl

Director, AI Governance

Dallas, TX · On-site

$156K - $296K/yr

Familiarity with AI model lifecycle governance, responsible AI principles, and regulatory frameworks (e.g., EU AI Act, NIST AI RMF). * Demonstrated success leading enterprise councils or cross ...

Lantern

Director, Application & AI Security

Dallas, TX · On-site +1

$58 - $77.75/hr

... AI RMF, ISO/IEC 42001). * Own security architecture and threat modeling, including secure-by-design review and ownership of cryptographic standards. * Own DevSecOps and pipeline security, with ...

Lantern

Director, Application & AI Security

Dallas, TX · On-site

$58 - $77.75/hr

... AI RMF, ISO/IEC 42001). * Own security architecture and threat modeling, including secure-by-design review and ownership of cryptographic standards. * Own DevSecOps and pipeline security, with ...

Roberthalf

Security of AI Associate Director

Dallas, TX · On-site

OWASP Top 10 for LLMs, NIST AI RMF, MITRE ATLAS, EU AI Act, and sector-specific AI risk guidance * Track record of owning client relationships and managing multi-workstream engagements from kickoff ...

Protiviti

Security of AI Associate Director

Dallas, TX · On-site

OWASP Top 10 for LLMs, NIST AI RMF, MITRE ATLAS, EU AI Act, and sector-specific AI risk guidance * Track record of owning client relationships and managing multi-workstream engagements from kickoff ...

previous pagenext page

Showing results 21-40

All JobsAi Rmf JobsAi Rmf Jobs in Grand Prairie, TX

Ai Rmf information

See Grand Prairie, TX salary details

$32.7K

$90.9K

$155.2K

How much do ai rmf jobs pay per year?

As of Sep 3, 2026, the average yearly pay for ai rmf in Grand Prairie, TX is $90,914.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,600.00 and $109,300.00 per year, depending on experience, location, and employer.

What is an AI RMF professional?

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 are some common challenges faced by AI RMF professionals?

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 the key skills and qualifications needed to thrive as an 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 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 Grand Prairie, TX?

For Ai Rmf jobs in Grand Prairie, TX, the most frequently searched job titles are:

What job categories do people searching Ai Rmf jobs in Grand Prairie, TX look for?

The top searched job categories for Ai Rmf jobs in Grand Prairie, TX are:

What cities near Grand Prairie, TX are hiring for Ai Rmf jobs?

Cities near Grand Prairie, TX with the most Ai Rmf job openings:

Ai Rmf jobs near you

AI Engineering Lead Agentic System

Select Minds LLC

Dallas, TX • On-site

$170K - $180K/yr

Full-time

Re-posted 4 days ago

Key responsibilities

  • Design and implement scalable agentic AI frameworks, including multi-agent orchestration, task planning, and execution pipelines.

  • Architect secure protocols and integrations to enable seamless agent-to-agent and agent-to-human collaboration.

  • Define and execute the roadmap for agentic AI solutions, evaluating and adopting emerging frameworks.

Job description

Benefits:
  • Long Term
  • Competetive Salary
  • Oppurtunity for Advancement

AI Engineering Lead – Agentic Systems                                     
Work Type: Full-Time, Onsite                              
Location: Dallas, Texas             
Interview Mode: In-Person
Work Auth : Must be authorized to work in the U.S.
Domain: Enterprise AI / Agentic AI / AWS Bedrock
Compensation: Competitive, commensurate with experience

Role Overview
As Tech Lead, Agentic AI Solutions, you will lead the design and delivery of enterprise-grade agentic AI architectures that enable autonomous and semi-autonomous agents to perform complex, cross-functional business tasks.
You will define the frameworks, orchestration patterns, and governance standards that ensure our agentic AI systems operate with safety, reliability, and scalability across enterprise environments. This position blends deep technical leadership with innovation in AI orchestration, distributed systems, and multi-agent coordination.
This is an ideal opportunity for an experienced technologist who thrives in a dynamic environment and is passionate about shaping the next generation of intelligent agent platforms within the enterprise.
Key Responsibilities
  • Architect & Lead Development: :Design and implement scalable agentic AI frameworks, including multi-agent orchestration, task planning, and execution pipelines.
  • Integration & Protocol Design: Architect secure protocols and integrations—such as Model Context Protocol (MCP) servers, API gateways, and tool registries—to enable seamless agent-to-agent and agent-to-human collaboration.
  • Technical Roadmap Ownership: Define and execute the roadmap for agentic AI solutions, continuously evaluating and adopting emerging frameworks like LangGraph, Bedrock Agents, CrewAI, and Strands.
  • Reusable Registries: Establish governed agent, prompt, and tool registries for standardized, reusable components.
  • Reliability & Performance: Engineer high-reliability orchestration with low latency, intelligent fallback, and self-healing mechanisms.
  • Observability & Governance: Implement traceability, explainability, and observability tools to ensure transparent, auditable agentic workflows.
  • Security & Compliance: Define security standards for API access, RBAC, data sanitization, and policy-gated tool execution; ensure compliance with NIST AI RMF, ISO/IEC 42001, and privacy-by-design principles.
  • Monitoring & Evaluation: Develop real-time monitoring pipelines that track agent decision quality, execution success/failure, and dependency health.
  • Cross-Functional Collaboration: Partner with Product Managers, Data Engineers, Legal/Compliance, and Business stakeholders to translate strategic objectives into robust agentic capabilities.
  • Innovation: Advance methods in planning, memory, context engineering, and knowledge integration to enhance autonomy, reliability, and reasoning capabilities.
  • Technical Leadership: Mentor engineers, promote best practices in AI infrastructure, and guide teams in developing modular, scalable, and compliant agentic systems.

Required Qualifications
Education:
Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
Experience:
  • 8+ years of software engineering experience in AI/ML, distributed systems, or platform engineering.
  • 3+ years in senior technical leadership or architecture roles guiding multi-disciplinary teams.
Technical Expertise:
  • Strong proficiency in Python and experience with multiple programming paradigms.
  • Deep experience with the AWS ecosystem (Bedrock, SageMaker, Lambda, S3, Redshift, VPC).
  • Proven ability to design agent-safe protocols (MCP, API sandboxes, secure tool registries).
  • Expertise in distributed systems, asynchronous processing, and low-latency orchestration.
  • Hands-on experience with AI observability and traceability systems.
  • Familiarity with metadata management, data lineage, and knowledge graph integration for agent context enhancement.
  • Leadership & Governance:
  • Skilled in agile methodologies and iterative delivery of complex AI infrastructure.
  • Demonstrated success implementing AI governance and compliance frameworks.
  • Exceptional ability to communicate complex technical concepts to both engineers and executives.
  • Strong track record of mentoring, team building, and fostering inclusive, high-performing teams.
  • Preferred Qualifications
  • Experience with LangChain, LangGraph, Bedrock Agents, CrewAI, or LLMOps frameworks.
  • Knowledge of GraphRAG, memory management, and context-aware planning in multi-agent systems.
  • Exposure to regulated environments such as healthcare, finance, or aviation.
  • Familiarity with AI risk management, auditability frameworks, and policy-driven AI governance.