Associate Director AI Prog Off

Responsibilities 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. Job requirements Minimum Qualifications, Education and Experience Required Qualifications Bachelor’s degree in Computer Science, Engineering, Health Informatics, Information Systems, Business Administration, or a related field (Master’s or MBA preferred). 8+ years of progressive leadership in technology program management, technology strategy, enterprise architecture, or IT risk/compliance, including 3+ years driving enterprise-wide technical transformation programs. Proven track record operationalizing technology, data, or AI governance programs within regulated environments (Healthcare, Life Sciences, MedTech, or Financial Services). Deep understanding of modern generative AI, agentic frameworks, LLM architectures, and associated risks (data leakage, IP exposure, bias, hallucination, non-deterministic behaviors). Familiarity with API gateways, identity and access management (IAM), data loss prevention (DLP), and cloud network access policies. Exceptional communication skills with demonstrated success aligning cross-functional executives across Engineering, Clinical Operations, Legal, Compliance, and Finance. Preferred Qualifications Direct background in digital health, radiology/medical imaging, or medical software environments subject to FDA (SaMD), HIPAA, SOC 2, or GxP regulations. Hands-on experience establishing AI FinOps, token consumption governance, or showback/chargeback models across multiple subsidiaries or business units. Relevant certifications such as IAPP Certified Artificial Intelligence Governance Professional (AIGP), CIPP, CISM, PMP, or SAFe Agilist. Direct experience negotiating enterprise AI software agreements and vendor terms. Quality Standards Communicates, cooperates, and consistently functions professionally and harmoniously with all levels of supervision, co-workers, visitors, and vendors. Demonstrates initiative, personal awareness, professionalism and integrity, and exercises confidentiality in all areas of performance. Follows all local, regional and country laws concerning employment. Follows all DeepHealth policies and procedures. Follows data privacy, compliance, safety and confidentiality standards at all times. Practices universal safety precautions. Promotes good public relations on the phone and in person. Adapts and is willing to learn new tasks, methods, and systems. Reports to work regularly as scheduled; consistently punctual with respect to working hours, meal and rest breaks, and maintains satisfactory personal attendance in accordance with DeepHealth guidelines. Completes job responsibilities in a quality and timely manner. Travel This position requires domestic/international travel up to 15%. Working Environment Remote / Hybrid #J-18808-Ljbffr RadNet