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Executive Medical Artificial Intelligence Jobs (NOW HIRING)

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Executive Medical Artificial Intelligence information

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$26.5K

$93.6K

$184K

How much do executive medical artificial intelligence jobs pay per year?

As of Aug 1, 2026, the average yearly pay for executive medical artificial intelligence in the United States is $93,552.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $120,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Executive in Medical Artificial Intelligence, and why are they important?

To thrive as an Executive in Medical Artificial Intelligence, you need expertise in healthcare, AI technologies, strategic leadership, and typically an advanced degree in a relevant field such as medicine, computer science, or biomedical engineering. Familiarity with machine learning platforms, regulatory compliance systems (like HIPAA), and data analytics tools is essential, as is experience with certifications in project management or AI ethics. Exceptional communication, visionary leadership, and the ability to foster cross-disciplinary collaboration are standout soft skills for this role. These skills and qualities are crucial for driving innovation, ensuring patient safety, and successfully integrating AI solutions into complex healthcare environments.

What is the difference between Executive Medical Artificial Intelligence vs Medical Data Scientist?

AspectExecutive Medical Artificial IntelligenceMedical Data Scientist
Required CredentialsAdvanced degrees in AI, healthcare, or related fields; experience in AI developmentMaster's or PhD in Data Science, Statistics, or related fields; healthcare data experience
Work EnvironmentHealthcare tech companies, hospitals, research institutionsResearch labs, healthcare organizations, tech firms
Employer & Industry UsageHealthcare AI solutions, medical device companies, hospitalsData analysis, predictive modeling, healthcare research
Common Search & Comparison IntentUnderstanding executive roles in healthcare AIData analysis in medical contexts

Executive Medical Artificial Intelligence professionals focus on leading AI initiatives in healthcare, often with strategic and managerial responsibilities. Medical Data Scientists analyze healthcare data to develop models and insights. While both roles require strong technical skills, Executive Medical Artificial Intelligence roles emphasize leadership and AI strategy, whereas Medical Data Scientists focus on data analysis and modeling.

What is an Executive Medical Artificial Intelligence?

An Executive Medical Artificial Intelligence is a senior-level professional who leads the development and implementation of AI technologies in healthcare organizations. They oversee strategies to integrate machine learning and data-driven tools into medical operations, aiming to improve patient care, clinical decision-making, and operational efficiency. This role requires a deep understanding of both healthcare systems and advanced AI methodologies, as well as leadership skills to manage interdisciplinary teams and ensure compliance with regulations. Executives in this field often collaborate with clinicians, data scientists, and IT professionals to drive innovation and maintain ethical standards.

How does an Executive Medical Artificial Intelligence professional typically collaborate with clinical and technical teams to implement AI solutions in healthcare settings?

An Executive Medical Artificial Intelligence professional plays a pivotal role in bridging the gap between healthcare providers and technical AI teams. They regularly engage with clinicians to understand medical needs, then work with data scientists and engineers to ensure AI solutions are clinically relevant, ethical, and compliant with healthcare regulations. Effective communication, cross-functional meetings, and iterative feedback cycles are essential for aligning project goals and ensuring successful integration of AI tools in real-world clinical workflows. This collaborative approach helps drive innovation while maintaining patient safety and data privacy.
More about Executive Medical Artificial Intelligence jobs
What cities are hiring for Executive Medical Artificial Intelligence jobs? Cities with the most Executive Medical Artificial Intelligence job openings:
What are the most commonly searched types of Medical Artificial Intelligence jobs? The most popular types of Medical Artificial Intelligence jobs are:
What states have the most Executive Medical Artificial Intelligence jobs? States with the most job openings for Executive Medical Artificial Intelligence jobs include:
What job categories do people searching Executive Medical Artificial Intelligence jobs look for? The top searched job categories for Executive Medical Artificial Intelligence jobs are:
Infographic showing various Executive Medical Artificial Intelligence job openings in the United States as of July 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $93,552 per year, or $45 per hour.

Artificial Intelligence Specialist

DirectedLINK LLC

Norwalk, CA

$60 - $86/hr

Full-time

Posted 17 days ago


Job description

Title: Artificial Intelligence (AI) Implementation Specialist

Employment Type: Contract, 12–24+ months

Compensation: $60–$86 per hour

Location: Norwalk, CA

Work Model: Onsite, 8:00 a.m. to 5:00 p.m. - 32hrs/weekly

Industry: Government / Public Sector


Company Overview

This large county government agency operates through more than 30 departments and delivers essential public services across a complex, highly regulated environment. The organization is advancing responsible and sustainable use of artificial intelligence to improve operations, service delivery, workforce productivity, decision-making, and technology capabilities.


Position Summary

The Artificial Intelligence Implementation Specialist works under the direction of an IT Manager, Project Manager, Department Executive, or user agency personnel. The Specialist helps departments evaluate, plan, implement, govern, and mature artificial intelligence capabilities across business and operational functions. This advisory and implementation-focused role assesses readiness, identifies high-value use cases, establishes responsible-AI practices, delivers proofs of concept, supports adoption, and transfers knowledge to internal staff. Application development may be included as a use case but is not the primary purpose of the role.


Key Responsibilities

  • Partner with department leadership, business owners, technical teams, and user agency personnel to translate operational needs into practical and responsible AI solutions.
  • Conduct AI readiness assessments, opportunity assessments, business-process analyses, technology-environment reviews, and organizational capability evaluations.
  • Identify, evaluate, prioritize, and document AI use cases based on feasibility, risk, operational impact, public value, implementation complexity, and expected business benefits.
  • Develop AI strategies, implementation roadmaps, adoption plans, operating models, governance recommendations, and organizational change-management approaches.
  • Establish responsible-AI and governance practices aligned with recognized frameworks, including the NIST AI Risk Management Framework.
  • Recommend controls addressing data privacy, information security, accessibility, bias and fairness, transparency, accountability, human oversight, regulatory obligations, and validation of AI-generated work products.
  • Recommend enterprise AI platforms, tools, integration patterns, workflow automation approaches, and supporting cloud or technology services.
  • Design, oversee, and deliver AI proofs of concept, pilots, and production implementations.
  • Define success criteria, performance measures, validation procedures, acceptance standards, and business-value metrics for AI initiatives.
  • Assess and integrate AI capabilities with existing data sources, enterprise applications, identity and access management systems, collaboration platforms, and cloud environments.
  • Establish prompt-engineering standards, reusable prompt libraries, design patterns, data-handling practices, output-review procedures, and quality-control requirements.
  • Evaluate AI-generated and AI-assisted outputs for accuracy, security, privacy, bias, accessibility, maintainability, and fitness for purpose.
  • Apply AI tools in a controlled and policy-compliant manner consistent with departmental standards, security requirements, privacy obligations, ethical practices, and accessibility standards.
  • Advise on AI-assisted software development workflows when application development is an approved use case.
  • Coordinate with application developers and technical teams to validate AI-generated code, documentation, test artifacts, and related work products.
  • Facilitate workshops, discovery sessions, stakeholder meetings, executive briefings, demonstrations, training sessions, and feedback activities.
  • Prepare clear technical documentation, executive reports, governance standards, implementation guides, operating procedures, templates, training materials, and knowledge-transfer resources.
  • Define and measure AI adoption, operational performance, productivity improvements, business value, service-delivery outcomes, and return on investment.
  • Recommend continuous-improvement actions based on performance results, stakeholder feedback, risk findings, technology changes, and organizational priorities.
  • Provide hands-on mentoring, facilitation, documentation, and knowledge transfer to technical and non-technical staff.
  • Build internal capability so staff can independently sustain, govern, operate, evaluate, and expand AI solutions.
  • Establish and maintain cooperative working relationships with executives, managers, business users, project teams, technical personnel, and other stakeholders.
  • Communicate effectively with both executive and technical audiences through oral presentations, written materials, demonstrations, and structured recommendations.


Required Qualifications

  • Minimum of five years of experience within the last seven years leading or supporting enterprise technology, digital transformation, or organizational technology-consulting initiatives, including assessment, planning, implementation, and adoption of new technologies.
  • Minimum of three years of experience evaluating, implementing, and integrating artificial intelligence, generative AI, or intelligent automation solutions to improve business operations, service delivery, staff productivity, decision-making, or software delivery.
  • Minimum of two years of experience developing AI strategies, readiness assessments, opportunity assessments, implementation roadmaps, governance recommendations, responsible-AI recommendations, and executive-level recommendations.
  • Minimum of two years of experience designing and delivering AI proofs of concept, pilots, or production implementations.
  • Minimum of two years of experience validating AI-generated or AI-assisted work products for accuracy, security, privacy, and fitness for purpose.
  • Minimum of two years of experience partnering with executive leadership, business owners, project managers, cybersecurity staff, infrastructure teams, business analysts, and/or application developers on information technology initiatives.
  • Minimum of one year of experience providing training, facilitation, mentoring, documentation, or knowledge transfer to technical and non-technical staff to build internal capability.
  • Knowledge and experience with enterprise AI implementation, generative AI, large language models, and AI agents.
  • Experience with enterprise AI services such as Microsoft Copilot, Azure OpenAI, ChatGPT, Claude, Google Gemini, or comparable platforms.
  • Knowledge and experience conducting AI readiness assessments, business-process analyses, AI use-case identification and prioritization, implementation road mapping, AI adoption, and organizational change management.
  • Knowledge and experience with AI governance and responsible-AI practices, including risk management aligned with the NIST AI Risk Management Framework.
  • Knowledge of data privacy, information security, bias and fairness review, human oversight, accessibility, and validation of AI-generated work products.
  • Knowledge and experience with prompt-engineering standards, reusable prompt and pattern libraries, workflow automation, and process automation.
  • Experience integrating AI into existing business and technology environments, including data sources, enterprise applications, identity and access management, and cloud services.
  • Ability to develop standards, documentation templates, technical briefings, executive briefings, training curricula, and knowledge-transfer materials.
  • Ability to define and measure AI adoption, performance, business value, and return on investment and recommend continuous-improvement actions.
  • Clear oral and written communication skills.
  • Ability to establish and maintain cooperative working relationships with individuals contacted during the course of the work.
  • Ability to communicate effectively with both executive and technical audiences.
  • Bachelor’s degree in Computer Science, Information Systems, Information Technology, Artificial Intelligence, Data Science, Business Analytics, Public Administration, Organizational Change Management, or a closely related field.
  • Additional qualifying experience may substitute for the required education on a year-for-year basis.
  • A master’s degree in a closely related field may substitute for one year of the required general experience.
  • Ability to work onsite in Norwalk, California, Monday through Friday from 8:00 a.m. to 5:00 p.m.


Preferred Qualifications

  • Experience implementing AI capabilities within government, public-sector, regulated, privacy-sensitive, or highly governed operating environments.
  • Experience with Microsoft Power Platform and Power BI.
  • Experience with Microsoft Azure and Microsoft Entra ID.
  • Familiarity with the software development lifecycle.
  • Experience with AI-assisted development tools such as GitHub Copilot or Cursor.
  • Experience establishing enterprise prompt libraries, AI design patterns, reusable implementation standards, and validation frameworks.
  • Experience measuring AI adoption, operational performance, service-delivery improvements, business value, and return on investment.
  • Experience preparing executive-level AI recommendations, governance materials, implementation briefings, and decision-support documentation.