Top AI Ethics Jobs in Denver & Boulder, CO

Lead design and execution of an enterprise AI literacy program: set roadmap and metrics, build proficiency frameworks, create scalable learning experiences, embed Responsible AI governance, partner cross-functionally, track adoption, support certification, and represent the program externally.

The Director, Analytics Standards & Impact Measurement oversees AI/ML standards, quantifies analytics impact, and ensures compliance within commercial analytics initiatives.

Review, evaluate, and annotate AI-generated text, images, audio, and video; perform quality checks for accuracy and guideline compliance; identify edge cases and inconsistencies; contribute to dataset creation and calibration; provide feedback to improve annotation workflows and guidelines.

The role involves evaluating AI outputs, generating content, providing annotations, and ensuring quality through cultural and contextual awareness.

Create clear, structured rater guidelines, evaluation rubrics, and reviewer instructions for human evaluators across domains. Review and revise documentation to remove ambiguity, design scoring frameworks, handle edge cases, and collaborate with researchers and SMEs to ensure consistent, high-quality AI evaluations.

Lead enterprise-wide AI adoption by translating technical AI concepts for non-technical stakeholders, curating education and communications, partnering with change management and L&D, triaging requests, and building a team to drive measurable AI adoption across the organization.

Evaluate AI-generated coding interactions end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide clear, opinionated feedback, distinguish response quality levels, and help define best practices for AI-assisted developer workflows.

Design and build clinical-grade automated evaluation pipelines (LLM-as-judge + human review), define benchmarks, run rigorous experiments, partner with engineering to implement CI gates for accuracy, factuality, and safety, and publish findings to improve model robustness and reduce hallucinations.

Lead enterprise AI governance, risk management, and Responsible AI adoption. Oversee AI inventory, policy, risk lifecycle, regulatory compliance, vendor assessments, and integration of governance into business workflows. Partner with Legal, Compliance, Security, PMO, and business units to prioritize AI initiatives, report metrics and ROI, and advise executives and boards.

Sell AI services and SaaS to new and existing B2B clients across industries, build pipeline, manage accounts, record CRM data, present complex proposals, and explain AI regulations and standards (e.g., 42001, 42006). Maintain client relationships and ensure timely delivery and retention.