Head of AI Ethics & Responsible AI

Soledad Data Solutions; California (MO); On-site; USD 150,000 - 230,000; Full time

Job summary

Soledad is seeking a senior leader to own AI ethics and risk governance across research, engineering, product, and customer success. You will ensure autonomous decisioning systems are fair, auditable, and compliant with emerging regulations.

You will author and maintain the ethics framework, lead risk reviews for new products, monitor regulatory developments, and conduct customer-facing trust conversations. Collaboration with model bias experts and documentation teams is essential.

Qualifications

• JD or equivalent experience in technology law, policy, or AI governance.
• 7+ years at the intersection of law/policy and applied technology.
• Strong written communication — you can write a policy a non-lawyer can apply.
• Comfortable engaging deeply with technical teams and reading model evaluation reports.
• Experience with high-stakes review processes (privacy, security, model risk).

Responsibilities

• Author and maintain AI ethics framework, model risk policy, and incident playbooks.
• Lead the AI risk review process for new products, customers, and use cases.
• Track regulatory developments (EU AI Act, NIST AI RMF, sector-specific rules) and translate them into engineering requirements.
• Run customer-facing trust conversations — risk assessments, audits, and assurance reports.
• Partner with research on bias evaluation, red-teaming, and model documentation (e.g., model cards).

Skills

Policy drafting

AI governance

Regulatory compliance

Model risk

Cross-functional leadership

Technical literacy

Job description

Soledad is seeking a senior leader to own AI ethics and risk governance across research, engineering, product, and customer success. You will ensure autonomous decisioning systems are fair, auditable, and compliant with emerging regulations.

You will author and maintain the ethics framework, lead risk reviews for new products, monitor regulatory developments, and conduct customer-facing trust conversations. Collaboration with model bias experts and documentation teams is essential.