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Leads enterprise AI governance, portfolio strategy, intake, prioritization, roadmaps, and lifecycle management across UL organizations. Partners with business, technology, legal, security, risk, compliance, finance, HR, vendors, and external partners to operationalize responsible AI, evaluate delivery approaches, measure value, manage adoption, and drive AI literacy. Establishes operating frameworks, governance processes, performance metrics, change programs, and sustainable AI implementation strategies.

The Receptionist serves as the primary contact for visitors, staff, callers, and collaborators while providing front-desk and administrative support. Responsibilities include managing communications, mail, shipping and receiving, meeting logistics, filing systems, office supplies, procurement requests, travel arrangements, events, building liaison activities, and office access credentials. The role also supports office cleanliness, organization, security administration, and daily operational readiness.

The Solutions Architect will design and manage technical solutions that align with business objectives, advocate for partner needs, evaluate technology platforms, and ensure solutions meet security and compliance requirements.

Provides confidential executive and administrative support to the Vice President of Research and Electrochemical Safety team. Responsibilities include complex calendar and travel management, meeting and event coordination, correspondence and briefing preparation, records and report maintenance, budget and expense tracking, presentation development, meeting-note synthesis, and liaison support across stakeholders.

Provide administrative and financial support for FSRI: process and reconcile expenses, handle purchasing and invoices, organize financial records, assist with budgets and variance reports, prepare financial summaries and presentations, and support contract and budgeting processes.

Lead full‑stack development of complex research platforms, set technical direction and architecture, integrate data pipelines and evaluation frameworks, mentor engineers, promote AI-assisted engineering practices (e.g., Claude Code), assist hiring/onboarding, and represent technical work across teams to deliver scalable, secure software for digital safety research.

Lead and execute independent research programs on NLP and LLM safety, design and run experiments, secure funding, publish and present results, lead cross-functional teams, and develop evaluation tools and challenges to advance digital safety.

Manage end-to-end technical project lifecycles for Digital Safety: define scope, plans, budgets, and risks; coordinate cross-functional teams and external partners; run status meetings, change control, compliance, stakeholder communication, and lessons-learned; deliver projects on time and within budget.

Design, develop, and evaluate AI safety assessment systems focused on LLMs and NLP. Investigate incident reports, conduct literature reviews, create and run NLP/LLM assessments, code or train text analytics, document methods, publish research, and collaborate with engineering teams to scale assessment tools.