AI Specialist

The Role
The AI Specialist partners with senior leadership and the data team to integrate AI across the business. This role leads internal Microsoft Copilot Studio initiatives while also supporting external, client-facing AI projects.

The focus is on defining and executing an internal AI roadmap, building scalable Copilot Studio solutions, and positioning the team as a forward-thinking, AI-enabled organization.

Key Responsibilities
Internal Copilot Enablement & Business Advisory (70%)
Partner with leaders across Data Engineering & BI, Acquisitions, Asset Management, Investor Operations, Fundraising, Marketing, and other teams to identify workflows suited for AI automation within Microsoft Copilot Studio
Conduct workflow interviews, discovery sessions, and process mapping to quantify efficiency gains
Build, test, and deploy Copilot agents, tools, prompts, automations, and plugins tailored to each department
Translate business requirements into structured prompts, datasets, templates, and agent behavior designs
Create repeatable playbooks and standards for Copilot usage, governance, and safe deployment
Train teams through workshops, documentation, and hands-on enablement
External AI Innovation & Strategic Projects (30%)
Partner with the SVP to develop external, AI-enabled client-facing tools (e.g., knowledge bots, portals, automated content systems)
Assist with market research, vendor evaluation, proofs of concept, and AI solution integrations
Participate in AI regulatory, compliance, and data governance discussions to support enterprise-grade deployment
Contribute to external demos, presentations, and AI strategy messaging for clients and firm leadership


Must-Have Skills & Experience
AI, Automation & Technical
Deep expertise with Microsoft Copilot, Copilot Studio, prompt engineering, and AI agent frameworks
Experience designing domain-specific prompts, structured queries, and multi-step agent workflows
Working knowledge of Power Automate, SharePoint integrations, Teams plugins, Microsoft Graph, and Fabric
Understanding of data classification, privacy, retrieval-augmented generation (RAG), and responsible AI practices
Comfortable working with APIs, reading JSON, and integrating systems
Ability to perform light data preparation or collaborate closely with Data Engineering and BI teams
Business Analysis & Product Thinking
Strong experience in requirements gathering and workflow mapping
Ability to translate abstract business needs into practical AI-enabled solutions
Proven approach to running pilots, documenting outcomes, and iterating quickly
Communication & Stakeholder Management
Ability to explain AI concepts in clear, practical terms to non-technical stakeholders
Comfortable leading training sessions and driving adoption across teams
Strong presentation skills; able to support the SVP in external-facing AI messaging
Mindset & Work Style
Curious, experimental, and quick to learn emerging AI tools
Comfortable operating in ambiguous, fast-moving environments
Highly collaborative across business and technical teams
Strong ownership mindset with the ability to execute independently
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