Responsibilities
- Translate Flagship's enterprise AI strategy into function-level execution by partnering with leaders across the firm on AI roadmap creation and delivery.
- Run a regular cadence of engagement with each business and scientific function to surface, intake, and prioritize use cases.
- Partner with the AI engineering team to shape use cases, supporting use case owners in identifying the right data, technology, and stakeholders for efficient and effective design.
- Track use case value/ROI throughout the life cycle and for the AI program overall.
- Drive solution reuse across functions by maintaining visibility into what has been built, by whom, and what is reusable.
- Operate the AI Operational Governance Forum by surfacing relevant AI product, feature, and use case developments and supporting decision-making and tracking around risk management.
- Support the evolution of Flagship’s AI strategy, policies, and roadmap by staying up to date on relevant industry trends and internal needs.
- Design and execute AI learning programs across the company that drive adoption while shaping responsible, secure, and cost-effective use of AI.
- Build and oversee operations for the AI change champion network to scale AI adoption.
- Develop reusable AI enablement assets and partner with Communications and Learning & Development to amplify.
- Provide hands-on coaching to teams adopting AI tools across the business.
- Provide support on AI tool evaluation, procurement, and lifecycle management across enterprise-wide and function-specific applications.
- Support ownership, administration, and governance of core enterprise AI platforms, including settings configuration, feature rollout, internal communications, and ongoing user support.
- Support vendor relationships and contracts in partnership with Procurement and Legal; track usage, license utilization, and consumption against contracted commitments.
- Coordinate with InfoSec on AI-specific risk reviews, ZDR posture, agentic sandbox governance, and shadow AI monitoring.
- Maintain the AI tool intake and approval process and the AI Product / Use Case records in Flagship's GRC system of record.
Requirements
- At least 5 years of progressive experience in technology, AI, digital transformation, or management consulting roles, including meaningful recent experience leading enterprise AI, digital, or technology enablement initiatives.
- Hands-on AI fluency. Power user of leading LLM platforms (Claude, ChatGPT, Gemini) with practical understanding of capabilities, limitations, and appropriate use by task type. Comfortable rapidly prototyping with low-code tools and AI features.
- Agentic AI fluency. Working understanding of agentic AI concepts and current capabilities, including autonomous and long-running agents, multi-step tool use, MCP and connector ecosystems, and human-in-the-loop design patterns. Able to evaluate where agentic approaches are appropriate, where they introduce risk, and how to deploy them safely.
- Use case portfolio management. Demonstrated experience running structured intake, prioritization, and ROI tracking processes for AI or digital initiatives across a federated organization.
- Vendor and tool management. Experience evaluating, contracting, and administering enterprise SaaS, ideally including AI/LLM platforms. Comfort working with Procurement, Legal, and InfoSec on contract review, DPAs, and risk assessments.
- Enablement and program delivery. Track record running training programs, hackathons, or change management initiatives for non-technical audiences at scale.
- Cross-functional execution. Demonstrated effectiveness operating without direct authority across IT, InfoSec, Legal, Finance, HR, and business stakeholders.
- Communication. Strong written and verbal communication; able to translate between technical and business audiences and produce executive-ready materials.
- Client-facing experience. Previous experience in a client-facing consulting, customer success, or IT business partner role.
- Bachelor's degree in a technical, business, or scientific field.
Nice to Have
- Prior experience in life sciences, biotech, or healthcare; comfort with the regulatory and IP-sensitivity considerations of these sectors.
- Experience administering Claude Enterprise, ChatGPT Enterprise, or M365 Copilot at scale.
- Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and GxP / research integrity considerations.
- Experience with MCP servers, agentic platforms, and AI workflow automation tools (Zapier, Workato).