Top AI Ethics Jobs in Chicago, IL

Provides global technical leadership for digital AI standards, certification, assurance, training, advisory, and assessment services. Develops AI governance and lifecycle assurance methodologies covering predictive and generative AI, LLMs, agents, cloud AI, model risk, testing, transparency, fairness, privacy, security, robustness, and operational resilience. Translates regulations, standards, emerging technologies, and customer needs into scalable offerings while engaging customers, regulators, standards bodies, and internal stakeholders.

Own and deliver high-value AI use cases end-to-end by embedding in business workflows, partnering with AI engineering pods, ensuring integrations (SAP, Salesforce, Databricks, Distyl), driving adoption, measuring business outcomes, and enforcing Responsible AI, security, and governance standards.

Design and deliver custom AI-driven legal workflows, implement and scale post-sales solutions, define KPIs and success metrics, inform product strategy, partner with Customer Success to demonstrate ROI, and maintain objective, ethics-compliant processes and playbooks for plaintiff law firms.

Lead strategy and architecture for the enterprise knowledge/context layer powering AI: set standards, control models, connector strategy, and federated operating models. Ensure content is AI-ready, permissions-aware, and measurable for retrieval and grounding. Partner with IT, Engineering, Legal, Privacy, and Security to define eligibility, sensitivity, and lifecycle policies and drive adoption across domains.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

Lead Vizient’s enterprise AI adoption and enablement strategy by creating scalable training, governance, engagement, solutioning, and measurement frameworks. Partner with technology, product, learning, communications, and change management leaders to align AI initiatives with business priorities, drive adoption, measure value, and influence senior stakeholders. The role also includes executive communications, strategic recommendations, and leadership of up to two direct reports.

Leads the enterprise AI portfolio, including use-case prioritization, investment governance, executive reviews, and strategic planning. Develops AI governance frameworks, policies, operating models, and accountability processes while partnering with business, technology, finance, risk, legal, compliance, and security teams. Establishes methods to measure adoption, ROI, and business value; leads AI literacy, training, communications, change enablement, and AI Champion initiatives; and delivers executive reporting on portfolio performance and outcomes.

Leads enterprise AI governance, responsible AI, technology risk, regulatory readiness, control management, governance automation, and operational excellence. Establishes AI lifecycle controls, decision rights, compliance processes, audit readiness, risk frameworks, and executive reporting. Partners across Legal, Compliance, Security, Data, Technology, and business teams to enable safe AI adoption, improve governance workflows, measure value realization, and build a high-performing multidisciplinary team.

Co-lead a new 10-week AI safety replication program: select replication targets, mentor fellows, take technical ownership of replications, set publication standards, represent the program externally, and support fundraising and long-term planning. Work includes experimental design, review, writing, and coordination with XLab operations.

Leads enterprise Responsible AI governance, overseeing AI and Generative AI risk assessments, fairness testing, model evaluations, monitoring, controls, and lifecycle governance. Advises business, technical, legal, compliance, and risk stakeholders; develops scalable governance frameworks; and evaluates emerging technologies such as foundation models and agentic AI. Drives controls for monitoring, human oversight, intervention, containment, and system shutdown while balancing regulatory obligations, risk management, innovation, and business value.