Top AI Ethics Jobs in Chicago, IL

The AI Governance Analyst will manage AI risk assessments, maintain AI governance frameworks, and ensure compliance with regulations, while coordinating with stakeholders and producing reports.

Lead AI safety strategies for autonomous vehicles, ensuring compliance with safety standards, mentoring teams, and guiding technical projects in AI/ML development for safety-critical applications.

The Director of CX AI will develop and execute the AI roadmap for customer experience, evaluate tools, modernize workflows, and ensure responsible AI use.

The AI Quality Associate evaluates AI outputs for quality, develops benchmarks and rubrics, validates workflows, and collaborates with finance experts to ensure high-quality AI-assisted outputs.

The Senior Manager will oversee AI governance, assess risks, and collaborate with data science teams to embed responsible AI practices across the organization.

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 development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

The Senior Technical Director for AI UX at Rocket Software will define the AI-driven experience across products, focusing on collaborative and responsible AI integration in enterprise workflows. They will establish architectural frameworks, mentor engineers, and validate AI models with customers.

Lead design and implementation of safety and alignment architectures for agentic AI systems; develop monitoring, reward modeling, and human-in-the-loop evaluation; partner with cross-functional teams for responsible deployment; publish research; identify and mitigate failure modes and set safety milestones for production readiness.

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