Top AI Ethics Jobs in Denver & Boulder, CO

Lead internal AI product strategy and operating model: set priorities for knowledge/context layers, reusable skills/agents, governance and trust, adoption and L&D strategy, partner with engineering, security, legal, and stakeholders to scale safe, company-wide AI practices and measure impact.

Own security and compliance for the Enterprise AI program by building security tooling, policy-as-code guardrails, reusable secure AI components, and observability to detect anomalous model behavior while partnering with Cyber Security and delivery teams.

Design HCI standards for Agentic AI products: create transparency and human-in-the-loop workflows, dynamic/generative and multi-modal interfaces, trust/error UX for hallucinations, prototype autonomous sequences with tools like Figma/Protopie, and organize dense information for auditability and oversight.

Own decision quality by evaluating AI-generated decisions, identifying reasoning failures, designing feedback and training loops, defining decision-quality metrics, and collaborating with Product, R&D, and Engineering to improve robustness, explainability, and drift detection.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Lead client-facing organizational change for AI and Workspace transformations: design change strategies, engage executives, build training and champion networks, run Gemini pilots, measure adoption, and sustain new behaviors across enterprises.

Lead Trust & Safety product efforts for AI-adjacent features: own product risk assessment, drive launch and operational readiness, translate safety needs into product requirements, build repeatable frameworks and tooling, partner cross-functionally to define mitigations and ownership, and establish a forward-looking roadmap for detection, escalation, and reporting systems to embed safety early in product development.

Lead the application of AI across the business by identifying use cases, building solutions, and driving adoption while ensuring responsible AI use.

The Enterprise Architect for Data & AI will shape the architecture for the SaaS platform, ensuring efficient data practices and responsible AI governance, while collaborating with various teams to align technology with business goals.

Lead enterprise AI opportunity discovery and architecture across business units, build ROI-driven business cases, evaluate and pilot AI tools and vendors, and partner with Engineering, Security, Legal, and Compliance to scale responsible AI solutions. Drive process discovery, solution design, vendor selection, and change management to translate strategic recommendations into measurable business outcomes.