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Senior, specialized AI leadership at a moderate-brand company reduces applicant density but remains visible to general AI candidates.
Requires deep AI, MLOps, and regulated defense-sector experience, limiting cross-industry transferability.
Requires deep MLOps, governance, vendor and security expertise, implying strict technical and domain filters.
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Own end-to-end strategy, solution design, and technical implementation of AI systems including MLOps/LLMOps pipelines ensuring scalability, maintainability, and integration.
Lead data governance, model evaluation, risk management, and compliance related to AI, including addressing fairness, security, and regulatory frameworks (e.g., GDPR, NIST).
Manage vendor/tool relationships, cross-functional stakeholders, and AI teams while driving performance monitoring, continuous improvement, and business impact assessment of AI deployments.
Experience Required: Not explicitly mentioned in the JD.
Must have expertise in AI/ML technical architecture including MLOps/LLMOps, vector databases, RAG pipelines, and cloud/on-prem model hosting.
Knowledge of AI-specific risk management, data governance, and compliance with data privacy regulations like GDPR, CCPA, and defense/public-sector frameworks such as NIST AI RMF or DoD AI ethics.
Proven experience managing cross-functional teams including data scientists and ML engineers; strong stakeholder management and vendor negotiation skills.
Strategic leader skilled at translating complex AI technical constraints into business terms and managing expectations on AI capabilities and limitations.
Experienced in operating within regulated environments (e.g., defense/public sector) ensuring security, ethical AI use, and compliance.
Strong technical ownership of AI solution lifecycles combined with team leadership focused on balancing experimentation and production discipline.