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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI architecturemachine learning architecturedata pipelinesorchestration frameworksmodel risk managementprompt engineeringvector databasesembedding pipelinesagent orchestration frameworksAI governance

Soft Skills

communication skillsmentoringcoachingstrategic thinkingcollaborationleadershipproblem-solvingsynthesis of complex topicsrelationship managementadvisory skills