Top AI Ethics Jobs in Denver & Boulder, CO

Lead AiLO portfolio integrating AI into K-12 systems: set strategy, design and draft high-stakes deliverables, manage complex projects, mentor teams, cultivate partnerships, and represent ILO externally to scale responsible AI adoption in education.

Supports responsible AI governance by developing frameworks, conducting fairness and risk assessments, monitoring regulatory requirements, maintaining compliance documentation, educating stakeholders, and improving AI oversight practices. Works across technical, legal, compliance, risk, and business teams to promote ethical, transparent, accountable, and trustworthy AI systems.

Leads research and thought leadership on AI-led go-to-market strategy and business transformation for small and midsize technology providers. Advises CEOs and executive teams on revenue architecture, sales, marketing, customer success, partnerships, pricing, operations, and converging AI technology stacks. Conducts market analysis, predicts trends, presents recommendations to clients and conferences, supports sales, reviews research, mentors colleagues, and improves research processes.

Manage the AI opportunity roadmap for Risk Services, prioritizing use cases, coordinating internal data science teams and external vendors, translating business needs into requirements, and supporting AI governance, compliance, explainability, auditability, implementation, adoption, and benefits realization. The role focuses on business outcomes and solution delivery rather than hands-on model development.

Perform human review and annotation tasks to train and evaluate AI: assess prompts and outputs, correct text, analyze multimedia, record voice samples, and provide structured annotations and culturally informed feedback following guidelines.

Conduct red teaming and adversarial evaluations of AI systems across violence, extremism, child safety, grooming, crisis, and other harm categories. Design evaluation frameworks, test scenarios, scoring criteria, taxonomies, and interventions that translate real-world harm expertise into structured technical outputs. Review model responses, exercise expert judgment, and produce methodology and findings for technical and government audiences while meeting ethical, legal, contractual, and data protection obligations.

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 end-to-end technical programs for AI safety research and infrastructure: scope plans, prioritize across teams, build compute/resource roadmaps, enable technology transfer, and coordinate internal stakeholders to accelerate research delivery.

Hybrid technical/customer-facing role building and refining AI risk-assessment modules using LLMs, writing SQL, and creating Power BI dashboards. Lead client onboarding, translate safety programs into the platform, partner on scoping and SOWs, serve as primary technical contact, QA AI outputs, and drive product improvements from client feedback.