??AI Platform Manager?

practical solutions to current challenges and creative, sustainable new approaches as technologies and university priorities evolve. ?We are a community of problem-solvers, innovators, and stewards of trust who take pride in building technology foundations that are reliable, secure, and designed for the future. We bring together technology expertise across academic, clinical, infrastructure, operations, research, and student domains, applying our knowledge of digital transformation and effective user experiences. Guided by our core values of innovation, integrity, collaboration, optimism, supporting success, and community-centered service, we?re not just maintaining technology-we?re shaping how it enables discovery, connection, and impact across the university and beyond. What You'll Do ??The AI Platform Manager is responsible for the day-to-day administration, governance, and continued development of Tufts University's enterprise generative AI platform. The position manages platform configuration, access, model availability, usage, costs, integrations, and vendor relationships while ensuring alignment with institutional requirements for security, privacy, accessibility, legal compliance, and responsible AI use. Working closely with technical teams and University stakeholders, the AI Platform Manager provides strategic leadership in shaping and advancing the University's AI ecosystem, translating emerging capabilities into secure, reliable, accessible, and well-governed services that support institutional priorities across teaching, research, administration, and innovation. The successful candidate will bring strong technical expertise in AI platforms, cloud infrastructure, system integrations, security controls, and service operations. This is a one-year limited term appointment with possibility of extension.? Platform Strategy and Governance Develop, maintain, and operationalize platform policies, standards, procedures, and user guidance in collaboration with the AI Tools Working Group and other University stakeholders. Recommend approved AI models, features, and default access levels for different audiences and use cases. Coordinate with Information Security, Privacy, Legal, Procurement, Accessibility, Research Technology, and data stewards to ensure that platform services and integrations meet institutional requirements. Develop and administer criteria for API access, external integrations, agent sharing, advanced coding tools, and connections to institutional systems or data. Participate in the review of higher-risk, specialized, or exception-based AI use cases. Contribute to the University?s broader AI governance, service strategy, and responsible-use practices. Platform Administration and Operations Manage platform configuration, institutional settings, users, groups, permissions, roles, model availability, storage allocations, and feature enablement. Oversee account provisioning and deprovisioning, access reviews, and administrative permissions. Coordinate the issuance, monitoring, rotation, and revocation of API credentials and other access keys in accordance with University security policies. Oversee token usage, sponsor accounts, user credits, budgets, storage limits, and departmental chargeback processes. Review and approve requests for increased usage, storage, model access, or other resources for courses, departments, research projects, and special initiatives. Coordinate the testing and release of new platform features, models, configurations, and updates before they are made broadly available. Monitor service availability, performance, security notifications, usage patterns, and overall platform health. Maintain operational, technical, and administrative documentation. Integrations and Service Development Coordinate the evaluation and implementation of platform integrations, including APIs, Model Context Protocol connections, identity and access management, coding tools, and connections to approved external systems. Gather and prioritize requirements for new models, integrations, features, and service enhancements. Work with technical staff to evaluate the feasibility, risk, cost, and service implications of proposed integrations and advanced use cases. Coordinate pilots, testing activities, and implementation projects involving new AI capabilities. Maintain project plans, decision records, issue logs, and service roadmaps. Contribute recommendations for the long-term development and sustainability of the University?s AI service ecosystem. Vendor and Partnership Management Serve as the primary operational contact with our AI platform providers. Manage implementation activities, service reviews, roadmap discussions, feature requests, issue escalation, upgrades, and ongoing vendor coordination. Track vendor commitments, open issues, planned releases, and service performance. Coordinate with procurement, legal, security, and other stakeholders on contract, compliance, and service-management matters. Develop an effective partnership model that enables timely escalation, knowledge sharing, and continuous improvement. User Support, Training, and Documentation Manage and respond to incidents, service requests, access requests, and special-project requests through established service channels. Troubleshoot platform issues in collaboration with technical staff, the Service Desk, and the vendor. Establish processes for ticket routing, escalation, resolution, and communication. Partner with AI proficiency and communications teams to support onboarding, demonstrations, workshops, office hours, and outreach. Provide guidance on responsible platform use, model selection, agent creation, API access, data handling, storage limits, and coding tools. Identify recurring issues and recommend improvements to documentation, training, configuration, or service design. Reporting and Continuous Improvement Monitor and report on platform adoption, model usage, costs, storage, service performance, and user feedback. Develop dashboards and reports for sponsors, administrators, service owners, and University leadership. Use operational and financial data to identify trends, forecast demand, and recommend changes to access, funding, support, or platform configuration. Conduct periodic reviews of models, permissions, integrations, policies, and resource allocations. Assessment of the platform?s value, effectiveness, sustainability, and alignment with University priorities. Successful TTS staff are known for effectively applied expertise, continuous learning, thoughtful attention to detail, timely and appropriately calibrated follow-up, proactive and constructive problem solving, openness to new approaches, and for building effective partnerships and trust within TTS, across the university, and (where relevant) with external partners. All TTS staff are expected to follow departmental shared administrative practices, including effective planning and communication around time off, attending required TTS and university trainings, and developing professional goals as part of the PDP planning process. TTS staff are also responsible for working in ways that align with the TTS vision statement and for being aware of and following individual group and department-wide shared practices. What We're Looking For Basic Requirements: Knowledge and experience typically acquired by: Bachelor's Degree in information technology, computer science, information science, higher education administration, or a related field, or an equivalent combination of education and relevant professional experience. 3-5 years of experience administering and managing enterprise technology platforms, cloud-based services, software-as-a-service applications, or other complex digital services. Experience managing users, permissions, system configuration, service requests, vendor escalations, and operational documentation. Experience coordinating work across technical and nontechnical stakeholder groups. Demonstrated ability to lead complex, high-level strategic programs across a diverse and multifaceted community of faculty, staff, and students. Strong project coordination, organizational, problem-solving, and customer-service skills Strong written and verbal communication skills, including the ability to explain technical concepts, policies, risks, and service requirements to nontechnical audiences. Preferred Qualifications: Experience administering generative AI, machine learning, API gateway, identity and access management, or cloud infrastructure services. Experience working in higher education, research, healthcare, or another decentralized and highly regulated organization. Familiarity with large language models, AI coding assistants, agent-building tools, APIs, Model Context Protocol, and retrieval-based AI systems. Pay Range Minimum $108,200.00, Midpoint $135,300.00, Maximum $162,400.00 Salary is based on related experience, expertise, and internal equity; generally, new hires can expect pay between the minimum and midpoint of the range.