Top AI Ethics Jobs in Denver & Boulder, CO

Lead product strategy and roadmap for enterprise data platforms, BI, analytics, and AI/ML products. Align investments with business priorities, partner with engineering and data teams, ensure governance and responsible AI, measure adoption and business impact, and build and mentor cross-functional product teams to drive platform adoption and value.

The Senior AI Risk Advisor will lead AI risk assessments, develop governance frameworks, evaluate AI vendors, and engage with stakeholders on AI adoption.

The AI Implementation Associate will drive AI adoption across all functions, integrate AI tools into workflows, and manage change. Responsibilities include creating AI agents, tracking performance metrics, and ensuring ethical AI use.

The AI Enablement & Governance Lead will establish and oversee AI governance, manage AI risk, and ensure compliance across the organization while collaborating with various departments to operationalize AI initiatives.

Evaluate Spanish-language responses for factual accuracy, identify misinformation or unsupported claims, and provide structured annotations following project guidelines. Maintain high quality, follow evolving instructions, and commit reliably to freelance remote tasks.

The Interaction Intelligence Program Manager leads the deployment of AI capabilities in the contact center, overseeing initiatives, technical oversight, and change management with a focus on ethical AI and stakeholder collaboration.

SoftSnow is seeking an AI Ethicist to define ethical guidelines, assess risks, and ensure compliance in AI implementations across various industries.

The AI Evals Lead will develop and manage eval benchmarks for AI systems, ensuring effective performance measurement and quality assurance through collaboration with engineering teams and industry partners.

As Director of AI Enablement, you will lead Apogee's AI strategy, managing program operations, cross-functional collaboration, governance, and performance measurement to drive organization-wide AI literacy and adoption.

Lead and execute design and operating effectiveness testing of data and AI governance controls, perform walkthroughs and artifact analysis, identify and document control issues, and provide risk-based advisory support to business and technology partners to improve control design and governance processes.