Associate Director, AI Program Office

About the role

DeepHealth is seeking an experienced leader to head the AI Program Office, driving enterprise‑wide AI adoption, governance, risk assurance, and cost management across its regulated healthcare and medical imaging platform.

Key responsibilities

• Design and operate an enterprise AI governance framework, including decision gates, review workflows, and escalation pathways.
• Author and maintain the AI Acceptable Use Policy, SOPs, data‑handling guardrails, and role‑based permissions.
• Curate a central registry of sanctioned AI models, platforms, and APIs; evaluate new tool requests and mitigate shadow‑AI usage.
• Conduct structured risk‑assessment intake for AI use cases, maintain algorithmic impact assessments, model cards, and audit logs.
• Define token allocation quotas, usage thresholds, and department‑level spend caps; build charge‑back/show‑back reporting.
• Lead enterprise‑wide AI adoption programs, prioritize high‑ROI use‑cases, and report KPIs to the CTO.
• Manage vendor relationships, negotiate contracts, and ensure compliance with data‑privacy and regulatory requirements.
• Develop role‑based AI curricula, prompt‑engineering playbooks, and provide internal consulting to turn business ideas into compliant AI solutions.

Required profile

• Bachelor’s degree in Computer Science, Engineering, Health Informatics, Business Administration or related field (Master’s/MBA preferred).
• 8+ years progressive leadership in technology program management or IT risk/compliance, including 3+ years driving enterprise‑wide transformation.
• Proven experience operationalizing AI governance in regulated environments (Healthcare, MedTech, Life Sciences).
• Deep knowledge of generative AI, LLM architectures, and associated risks.
• Strong communication skills and ability to align cross‑functional executives.

Required skills

• API gateways and access‑control configuration.
• Identity and Access Management (IAM) and Data Loss Prevention (DLP) technologies.
• Cloud network access policies and security controls.
• AI FinOps, token budgeting, and charge‑back models.
• Model cards, audit logging, and algorithmic impact assessment documentation.
• Familiarity with AI governance frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act, HIPAA, FDA SaMD guidance).