Stanford Law School needs to identify, evaluate, and implement state-of-the-art legal technology, specifically focusing on AI, to advance its teaching and research. This involves turning pedagogical goals into reliable, secure, accessible, and student-centered services while protecting privacy and equity, and ensuring emerging tools are responsibly and sustainably integrated.
Requirements
- Demonstrated experience in evaluating and implementing library technologies.
- Strong understanding of the legal technology landscape and emerging AI tools.
- Knowledge of data privacy and security best practices relevant to AI.
- Working knowledge of digital accessibility standards for instructional and public-facing tools.
- Familiarity with REST/GraphQL APIs, webhooks, and the Model Context Protocol (MCP) for connecting AI tools to campus systems; ability to write small integration scripts (Python/JavaScript) and lightweight UI glue (HTML/CSS).s integration.
- Experience configuring SSO (SAML/OIDC) and basic identity/permission models for SaaS tools.
- Working knowledge of LLM evaluation/guardrails and RAG concepts to scope and review vendor pilots (no model training required).
Responsibilities
- Lead AI tool governance: run intake reviews (security, privacy/FERPA, accessibility) with IT/General Counsel/SLS Leadership; document risks/mitigations pre-pilot.
- Operationalize the NIST AI Risk Management Framework (incl. the Generative AI Profile) for pilots and production; maintain an AI risk register.
- Own vendor & rollout management (e.g., Lexis+ AI, Westlaw Precision AI, Bloomberg Law, CoCounsel): pilot charters, success metrics, DPA/license coordination, SSO/configuration, comms, and training plans.
- Own the end-to-end rollout of new AI tools (e.g., Lexis+ AI, Westlaw Precision AI): draft a short pilot plan, define success metrics, coordinate privacy/security and licensing with IT/Legal/Procurement, set up SSO/configuration, and provide training, quick-start guides, and a support path.
- Run AI red-team tests (prompt injection/jailbreak scenarios) and capture mitigations; verify vendor guardrails match SLS policy.
- For hosted or local/open-source LLMs, set up with IT: monitoring/usage analytics, secrets management, role-based access, and configuration aligned to policy.
- Build light automation/integration (APIs, small Python/webhook scripts) and maintain user-facing documentation/service catalog.
Other
- Advanced degree in Library Science (ALA‑accredited MLIS/MLS) or a relevant academic discipline by start date, or an equivalent combination of education and experience.
- Five or more years of relevant experience in an academic, law, or research library setting, or in a similar research-focused organization, with evidence of capacity to lead at a high level of responsibility.
- Proven ability in project management and service development.
- Demonstrated experience in or strong desire to learn instructional design, teaching, and pedagogical best practices.
- Interpersonal Skills: Demonstrates the ability to work well with colleagues and clients and with external organizations.
