The AVP, AI Solutions Architect is responsible for the configuration, integration, and practical deployment of enterprise AI tools across the organization. This role owns the technical delivery of AI capabilities, from platform administration and API governance through to the design of reusable assets that enable business teams to embed AI into their workflows effectively and at scale. Supporting both technical and non-technical users across a diverse portfolio of business domains spanning investment, actuarial, finance, and risk functions, the AI Solutions Architect serves as both a hands-on practitioner and a trusted technical advisor, ensuring that AI tools are adopted consistently, responsibly, and with measurable impact. Decisions and recommendations made in this role have direct implications for the firm's AI risk posture, operational continuity, and the pace at which AI capabilities reach the business. 

Success in this role is defined by the adoption and effective use of AI platforms across the organization, the creation of reusable, scalable assets that reduce duplication and accelerate time-to-value, a reduction in risk and compliance issues associated with AI tool usage, and the timely enablement of new AI capabilities as they become available. Beyond direct delivery, this role influences the firm's broader AI culture, shaping how business teams think about and approach AI adoption, and establishing the technical standards and patterns that govern AI use across the organization. The AI Solutions Architect operates with a high degree of autonomy in day-to-day technical decisions, and formally recommends tool approvals, configuration standards, and integration patterns to the AI enablement and governance functions. 

What You Will Do: 

• Administer enterprise AI platforms, including AI-native and AI-embedded systems, managing licenses, workspace configurations, access controls, and usage policies across the organization 

• Design and build reusable integration patterns, configuration templates, and AI-powered assets, including Custom AI Agents, Agentic Skills, and shared AI knowledge base Projects, that enable business teams to adopt AI capabilities consistently and without duplication of effort 

• Support the integration of AI tools into core business systems including Underwriting, Modeling, Ledger workflows, and other internal platforms, navigating both technical and process-level challenges 

• Provide hands-on technical guidance to business teams, helping them identify sound AI approaches for their use cases and implement them effectively, including advising on repository structure and development environment configuration for teams using AI coding assistants 

• Assess and apply emerging AI platform capabilities, including agent skills, agent teams, subagents, and Custom MCP integrations, evaluating their practical applicability and recommending adoption where appropriate 

• Govern API connectivity between AI platforms and internal systems, ensuring integrations are secure, well-documented, and maintained to enterprise standards 

• Identify and escalate risks associated with AI tool configurations and integrations, with particular attention to data handling, access controls, and regulatory compliance 

• Maintain accurate documentation of deployed tools, active pilots, and assessed capabilities, supporting governance and audit readiness 

What You Will Have: 

• Demonstrated experience administering and integrating enterprise SaaS or AI platforms at scale, with a track record of delivering end-to-end technical solutions in a complex organizational environment 

• Solid understanding of how modern AI tools function — including large language models, agents, tool use, and context management — applied with practical rather than purely theoretical intent 

• Intermediate knowledge of agentic AI concepts, including agent skills, subagents, agent teams, and orchestration patterns, and a demonstrated commitment to staying current as these evolve 

• Experience structuring codebases or development environments for use with AI coding assistants 

• A risk-oriented mindset, with the judgment to surface platform and integration risks proactively and engage constructively with risk, compliance, and security stakeholders 

• Solution-oriented approach with a client-centric mindset — focused on delivering outcomes that are practical, scalable, and genuinely useful to the business teams this role serves 

• Advanced communication skills, with the ability to translate technical AI concepts into clear, accessible language for general business audiences 

• Excellent collaboration and stakeholder management skills, with the ability to partner effectively across technical teams, business stakeholders, and control functions 

• The ability to guide and enable others, helping teams adopt AI capabilities through clear patterns, practical examples, and hands-on support 

• Comfort operating in fast-evolving technology environments, using judgement to balance experimentation with delivery 

• Hands-on experience building Custom AI Agents, Agentic Skills, or MCP-based integrations 

• Familiarity with AI governance principles as applied to enterprise tool deployment 

• Prior experience in a regulated industry, preferably financial services