Top AI Ethics Jobs in Denver & Boulder, CO

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Leads CDW’s AI advisory consulting portfolio, including strategy, governance, operating models, adoption, prioritization, and roadmaps. Develops consulting methodologies, delivery frameworks, sales enablement, and thought leadership. Advises executives and customers, leads complex presales pursuits, shapes proposals and business cases, oversees delivery quality and risk, evaluates technical feasibility, and mentors consulting and presales teams.

Lead AI product strategy and roadmap for Spectrum News. Translate editorial and business needs into product requirements, collaborate across teams, guide development of personalization, recommendations, discovery, and newsroom productivity AI features, ensure responsible AI governance, measure impact with analytics, and communicate vision to stakeholders.

Leads trust and safety for AI products serving teachers and students. Owns model guardrails, evaluations, red-teaming, monitoring, incident response, student-facing safety, district trust documentation, and regulatory alignment. Builds safety infrastructure into product development, manages incidents and postmortems, partners with Legal and Engineering, and leads a growing Trust & Safety team.

Lead Verizon’s enterprise Responsible AI program, including AI governance, risk frameworks, model audits, bias mitigation, explainability, red-teaming, regulatory compliance, and AI lifecycle controls. Chair governance reviews, establish deployment criteria, partner with legal, privacy, engineering, and product teams, and develop workforce training on AI ethics and responsible development.

Lead enterprise AI adoption by developing rollout plans, training programs, workflow playbooks, automation use cases, tool governance, acceptable-use policies, and risk controls. Measure adoption and business outcomes, manage an AI champions network, supervise a team, and partner with Security, Legal, Compliance, IT, Procurement, Product, and Engineering. The role focuses on safe, practical AI use across healthcare operations while addressing PHI, retention, vendor data use, HIPAA, and SOC 2 requirements.

Leads enterprise knowledge and AI transformation across Customer Success, Support, Enablement, Product, Operations, and Technology. Develops knowledge architecture, taxonomy, governance, metadata, content standards, ownership, and lifecycle processes. Builds AI-ready knowledge foundations for retrieval, self-service, copilots, and agentic workflows. Evaluates and implements AI opportunities, improves content and response quality using performance data, drives Knowledge-Centered Service practices, and leads cross-functional adoption and change without direct authority.

Advises enterprise executives on AI transformation for contact center and customer service operations. Develops AI strategies, roadmaps, business cases, operating models, and value realization frameworks. Leads executive workshops and defines use cases involving virtual agents, agent copilots, analytics, automation, and agentic AI. Evaluates platforms and technologies, provides vendor-neutral recommendations, and partners with clients, vendors, and delivery teams to guide successful implementation.

Lead end-to-end red-teaming campaigns against frontier AI models by defining threat models, designing attack scenarios and taxonomies, coordinating operators, and producing executive risk reports. Establish recurring testing cadences, track exploit families, measure severity and user harm, maintain dashboards, and partner with research, product, and operations teams to validate fixes and run regression tests.

Leads AI governance and assurance engagements, designing policies, controls, operating models, risk assessments, and compliance programs. Evaluates AI security, model governance, third-party solutions, and control effectiveness against frameworks including NIST AI RMF, ISO 42001, and the EU AI Act. Collaborates with security and engineering teams to test threats such as prompt injection, model manipulation, data poisoning, and leakage. Advises executives and clients, develops methodologies and proposals, researches emerging AI risks and regulations, and supports business development.