Top AI Ethics Jobs in Chicago, IL

Lead AI governance projects within Risk and Compliance, assess governance/risk/control programs, translate technical concepts for non-technical stakeholders, design and evaluate AI governance frameworks and controls, interpret data to inform recommendations, build client relationships, and mentor junior team members.

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.

Lead ownership of reliability, evaluation, and safety for an AI copilot in a trading platform. Build eval systems, benchmarks, automated quality gates, monitoring, and model improvement loops; partner with engineering and product to define safe tool contracts and ensure predictable, auditable assistant behavior in trading workflows.

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.

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 intake, roadmap, and governance for an AI automation/platform team. Harden and ship business-built AI apps to production with secure GCP platforms, define acceptance criteria and responsible-AI gates, manage vendor buy-vs-build decisions, drive adoption, measure outcomes, and manage AI economics and stakeholder communication.

Lead second-line operational risk reviews for AI and data risks, challenge first-line practices, perform risk/control assessments and gap analyses, advise business leaders, and support KPI/KRI monitoring and regulatory engagement.

Lead enterprise Responsible AI and AI Governance by developing frameworks, policies, controls, and evaluation standards. Oversee reviews of AI use cases, track KPIs/KRMs, advise and challenge teams on risk and compliance, engage stakeholders and regulators, and drive continuous improvement and enterprise adoption of ethical, transparent, and compliant AI practices.

Co-founder and CPTO will design and ship an explainable AI compliance platform: build architecture and security (SOC 2, tenant isolation, encryption, audit logging), deliver LLM/RAG-based production models with explainability and reliability, recruit and lead engineering/AI teams, convert pilots to customers and help scale to $1M ARR, and represent the company to customers and investors.