Ai Program Manager Jobs in Dallas, TX (NOW HIRING)

We are seeking a strategic and operationally focused AI Program Manager to lead cross-functional programs from vision to impact across a healthcare enterprise, partnering with the AI Product Owner to lead the end-to-end execution of AI initiatives, ensuring projects align with business goals.  The ideal candidate is a strong leader and critical thinker who excels at driving clarity, mitigating risk, and enabling teams to deliver business outcomes.

This role will bridge the gap between business stakeholders and technical teams, serving as the coordinator for AI solution delivery; partnering closely with clinical and operational stakeholders, finance, and procurement; and working with external vendors to pilot, scale, and monitor solutions with measurable return on investment. The individual must ensure potential AI solutions are compliant with regulations and Tenet policies. 

The AI Program Manager will not define the enterprise AI strategy or product roadmap; instead, this role is responsible for translating strategic direction into repeatable execution frameworks, governance processes, operational standards, and measurable outcomes. The ideal candidate combines healthcare operational knowledge, strong program management discipline, vendor management experience, and the ability to navigate cross-functional enterprise environments.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, Information Systems or appropriately relevant field
• 5+ years of program or project management experience managing technical programs in healthcare, specifically with data science, AI/ML environments, AI-enabled initiatives, or digital transformation
• Experience in program management methodologies (Waterfall, Agile, hybrid)
• Experience leading cross-functional enterprise programs involving clinical, operational, and technology stakeholders
• Experience managing pilots, proof-of-concepts, innovation initiatives, or emerging technology programs
• Strong understanding of healthcare operations, governance structures, and stakeholder management
• Demonstrated ability to establish operational processes, frameworks, and standardized methodologies
• Strong analytical, organizational, communication, and executive presentation skills

Preferred Qualifications

• PMP, Lean, Agile, or similar program management certifications preferred
• Experience supporting AI, automation, machine learning, generative AI, or advanced analytics initiatives
• Familiarity with clinical workflows, healthcare operations, and clinical informatics
• Experience working with enterprise portfolio management practices
• Experience in large, matrixed healthcare organizations

Success Profile

The ideal candidate is:

• Versed with AI advancements in generative AI, machine learning, etc
• Experienced working with healthcare data and familiar with healthcare regulations
• Adept at critical thinking; demonstrated ability to analyze information, question assumptions, and evaluate arguments to form well-reasoned judgments and solve problems effectively without relying on status-quo or others' direction
• Operationally disciplined and process-oriented; skilled at coordinating complex cross-functional initiatives
• Comfortable navigating ambiguity in emerging technology environments
• Able to balance innovation with governance and operational rigor
• Focused on measurable outcomes, adoption, and scalability
• Strong executive communication skills and C-Level interaction

Ability to travel ~ 25% depending on project need. Selected candidate will be required to pass a Motor Vehicle Records check.

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Stakeholder & Cross-Functional Alignment

• Partner closely with the AI Product Owner (who maintains responsibility for business case development, ROI modeling, roadmap planning, and governance direction) from ideation to implementation
• Align pilot execution activities with enterprise portfolio priorities and operational objectives
• Serve as a liaison between business operators, clinical informaticists, technical teams, vendors, and leadership stakeholders
• Facilitate executive and operational communications regarding pilot status, risks, outcomes, and adoption readiness
• Drive stakeholder engagement to ensure operational alignment, user readiness, and successful adoption
• Works collaboratively with business and technical stakeholders, regardless of reporting structure

AI Execution & Program Management

• Lead end-to-end coordination and execution of AI pilots and solutions across clinical, operational, and corporate functions
• Establish and maintain a standardized AI framework, including intake, evaluation, execution, measurement, adoption, and transition processes
• Develop repeatable methodologies, templates, and governance checkpoints for AI delivery
• Ensure solutions are delivered consistently with defined objectives, timelines, success criteria, and stakeholder accountability
• Bridges strategy and execution across initiatives to maximize efficiency and chance of achieving business goals
• Coordinate dependencies across portfolio management, operational teams, IT, security, legal, procurement, and finance
• Manage pilot lifecycle activities from initiation through operational handoff or closure
• Pro-actively develop and drive program delivery improvement

Vendor & Third-Party Engagement Management

• Oversee third-party AI vendor engagements, pilot coordination activities, and implementation timelines
• Monitor vendor deliverables, pilot performance, and adherence to enterprise standards and expectations
• Manage external partner relationships to ensure accountability and alignment with organizational objectives

Governance, Metrics & Operational Outcomes

• Track pilot performance metrics, KPIs, adoption indicators, operational outcomes, and value realization measures
• Partner with operators and clinical informaticists to evaluate workflow impact, user adoption, and measurable business outcomes
• Develop dashboards and executive reporting mechanisms to communicate pilot progress, risks, outcomes, and scalability recommendations
• Ensure pilots have clearly defined success criteria, measurable outcomes, and post-pilot evaluation processes

Adoption & Change Enablement

• Support organizational readiness and adoption planning for AI-enabled workflows and solutions
• Identify operational barriers, change impacts, and stakeholder concerns related to AI implementations
• Promote standardized processes and enterprise consistency in how AI pilots are introduced, managed, and evaluated
• Help establish sustainable operational models for successful pilots transitioning into broader deployment