Enterprise AI Architect

Role Overview

• Define and maintain the firm's Enterprise AI Architecture, spanning model infrastructure, data pipelines, orchestration layers, integration patterns, and governance controls
• Develop reference architecture for agentic AI systems and multi-agent workflows, establishing standards for orchestration frameworks, tool use, and model-context protocols (MCP) across business domains
• Develop AI reference architectures for accelerating priority investment front-to-back office use cases
• Drive integration of AI capabilities with core data platform and content platform, leveraging retrieval-augmented generation (RAG), MCP, etc. to unlock the firm's proprietary data assets
• Design and operationalize the AI governance framework, covering model risk management, explainability standards, bias monitoring, data lineage, and regulatory compliance (existing and emerging AI-specific regulation)
• Establish, evolve model evaluation and selection criteria for frontier and open-weight models, balancing capability, performance, cost, latency, etc.
• Partner with Legal, Compliance, and Risk to embed AI risk controls into architecture review processes
• Define data privacy and security patterns for AI workloads, including prompt injection defenses, PII handling, and sovereign data requirements
• Translate business strategies from investment management, distribution, finance, and operations into AI architecture requirements and roadmaps
• Guide Architecture Review Board (ARB) evaluations for AI-related proposals, ensuring alignment with enterprise standards, principles, and strategic direction
• Produce executive-grade artifacts — technology radars, strategic assessments, vendor evaluations, and architectural decision records (ADRs)
• Serve as an AI thought leader and trusted advisor, building AI literacy and architectural confidence across technology and business leadership
• Operate a continuous technology scanning practice, monitoring frontier AI developments (foundation models, agentic frameworks, AI infrastructure) and distilling insights for senior leadership
• Evaluate and pilot emerging AI capabilities in a structured proof-of-concept framework, with clear criteria for progression from exploration to production
• Maintain relationships with leading AI vendors, cloud hyperscalers, research institutions, and peer firms to benchmark capability and strategy
• Mentor and coach architects and engineers on AI design patterns, responsible AI practices, and architectural thinking
• Contribute to the development of the Enterprise Architecture practice, including standards, templates, and capability-building programs
• Represent the firm in external architecture and AI forums, industry working groups, and partner communities

Requirements

• Bachelor’s degree in computer science, engineering, mathematics, statistics or related fields
• 10+ years in technology architecture roles, with at least 3–5 years focused on AI/ML architecture in large, complex enterprise environments
• Deep, hands-on command of the modern AI stack: LLM APIs and fine-tuning, vector databases, RAG architectures, embedding pipelines, prompt engineering, and agent orchestration frameworks (LangChain, AutoGen, or equivalents)
• Practical exposure to agentic AI architecture, multi-agent coordination, and Model Context Protocol (MCP) or similar tool-use frameworks
• Proven experience with enterprise data platforms (Snowflake, Databricks, or comparable) and integrating AI capabilities on top of them
• Strong understanding of cloud-native architecture on AWS, including relevant AI/ML services, e.g. Bedrock, etc.
• Demonstrated ability to produce high-quality architecture artifacts — reference architectures, technology radars, ADRs, capability assessments
• Familiarity with enterprise architecture frameworks such as TOGAF, and experience operating within Architecture Review Boards
• Excellent communication skills: the ability to synthesize complex technical topics into clear, actionable narratives for non-technical stakeholders.

Tech Stack

• AWS
• Cloud

Benefits

• Competitive compensation
• Annual bonus eligibility
• A generous retirement plan
• Hybrid work schedule
• Health and wellness benefits, including online therapy
• Paid time off for vacation, illness, medical appointments, and volunteering days
• Family care resources, including fertility and adoption benefits