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Associate Director, AI Program Office (AI Office Lead)

🕒 3 days ago
AI GovernanceTechnology Program ManagementEnterprise ArchitectureRisk Compliance
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📜 Description

  • Direct the AI Program Office to enhance software engineering and workforce productivity.
  • Establish and maintain the enterprise AI governance framework and acceptable use policy.
  • Oversee the registry of sanctioned AI models and manage the evaluation of new AI tools.
  • Conduct structured risk assessments for AI use cases and maintain governance artifacts.
  • Define usage thresholds and monitor AI model performance and cost optimization.
  • Drive enterprise AI fluency through tailored training and promote responsible AI adoption.

🛠️ Requirements

  • Bachelor's degree in Computer Science, Engineering, Health Informatics, or related field; Master's or MBA preferred.
  • 8+ years of leadership in technology program management or IT risk/compliance.
  • 3+ years of experience in driving enterprise-wide technical transformation programs.
  • Proven track record in operationalizing AI governance in regulated environments.
  • Deep understanding of generative AI and associated risks.
  • Exceptional communication skills for cross-functional alignment.
Full job description

As artificial intelligence rapidly transitions from departmental experimentation to mission-critical operational infrastructure, DeepHealth requires an experienced, forward-looking leader to orchestrate enterprise-wide AI adoption, governance, risk assurance, and cost management. The Associate Director, AI Program Office serves as the single accountable leader bridging software engineering, product operations, enterprise productivity, and regulatory compliance.

Operating within the Office of the CTO, you will direct the AI Program Office across all major dimensions of enterprise AI utilization from software engineering acceleration and workforce productivity to autonomous operations and domain-specific applications. In our regulated healthcare and medical imaging environment, you will institute the operational standards, policies, and technical controls necessary to ensure that AI adoption remains safe, compliant, cost-effective, and directly aligned with measurable business value.

Enterprise AI Governance, Policy & Technical Controls

  • Architect, operationalize, and maintain the enterprise AI governance framework, establishing transparent decision gates, review workflows, and escalation pathways.

  • Author and maintain the enterprise AI Acceptable Use Policy, supported by SOPs, data-handling guardrails, and role-based permissions.

  • Translate policy into automated technical guardrails via API gateways, connector permissions, model endpoint access rules, and usage quotas.

  • Monitor emerging frameworks and legal mandates (NIST AI RMF, ISO/IEC 42001, EU AI Act, HIPAA, FDA SaMD guidance) and adapt internal compliance controls accordingly.

Tool Sanctioning & Central Registry

  • Own and curate the registry of sanctioned AI models, platforms, and API connectors across the organization.

  • Manage intake and multi-stakeholder evaluation of newly requested AI tools and capabilities.

  • Proactively identify, monitor, and mitigate unsanctioned “shadow AI” tools and integrations in partnership with Information Security.

  • Maintain onboarding standards so approved tools move from request to production quickly and safely.

Risk Review, Safety & Assurance

  • Run a structured risk-assessment intake for emerging AI use cases, internal prompts/fine-tunes, and third-party AI integrations.

  • Maintain complete governance artifacts, including algorithmic impact assessments, model cards, audit logs, and exception approvals.

  • Partner closely with:

    • Information Security

    • Legal

    • Privacy

    • Quality/Regulatory Affairs

  • Validate control effectiveness, address audit findings, and support customer and regulatory inquiries.

AI FinOps, Token Budgets & Cost Optimization

  • Define usage thresholds, token allocation quotas, and department-level spend caps across enterprise AI models and platforms.

  • Build and oversee enterprise AI visibility reporting to monitor usage patterns, token efficiency, license utilization, and latency metrics.

  • Design and operate an equitable cross-business-unit chargeback and showback mechanism, identifying consolidation and volume-discount opportunities.

Program Roadmap & Use Case Factory

  • Spearhead enterprise-wide adoption programs for core foundational platforms and emerging cognitive tools.

  • Prioritize use-case intake across clinical operations, corporate functions, and engineering to maintain a high-ROI implementation backlog.

  • Define KPIs and measure quantifiable outcomes, reporting program health directly to the CTO and executive leadership.

Strategic Vendor & Partner Management

  • Act as the primary relationship owner for technology partners, and emerging AI vendors.

  • Negotiate enterprise agreements, data confidentiality addenda (BAAs, zero-data-retention terms), license tiers, and performance SLAs in coordination with Procurement and Legal.

  • Manage contract renewals and performance reviews to ensure ongoing value and compliance.

Enablement, Training & AI Culture

  • Drive enterprise AI fluency through tailored role-based curricula, prompt-engineering playbooks, and interactive office hours.

  • Serve as an internal consultant for department heads and product teams, turning ambitious business ideas into practical, compliant AI implementations.

  • Promote a culture of responsible AI adoption in partnership with change management and communications teams.

PLEASE NOTE: This is not an exhaustive list of all duties, responsibilities and requirements of the position described above. Other functions may be assigned and management retains the right to add or change duties at any time.

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