Enterprise AI Architect

Role Summary

At T. Rowe Price, the mission of the Enterprise Architecture (EA) function is to empower the firm to achieve its strategic objectives through optimal use of technology. As Enterprise AI Architect, you will be at the forefront of firm‑wide AI activation, working directly with the Chief Architect to define, govern, and accelerate AI adoption across a complex, global institution, translating ambitious strategy into concrete architectural blueprints that are coherent, scalable, secure, and aligned with fiduciary obligations.

Responsibilities

• AI Architecture & Strategy: Define and maintain the 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 MCP and model‑context protocols. Create AI reference architectures for investment and front‑to‑back office use cases. Drive integration of AI capabilities with core data platforms and content platforms, leveraging RAG and MCP to unlock proprietary data assets.
• Governance & Risk: Design and operationalize AI governance, covering model risk management, explainability, bias monitoring, data lineage, and regulatory compliance. Evolve model evaluation and selection criteria for frontier and open‑weight models, balancing capability, performance, cost, and latency. Partner with Legal, Compliance, and Risk to embed AI risk controls into architecture review processes. Define data privacy and security patterns for AI workloads.
• Enterprise Alignment & Stakeholder Leadership: Translate business strategies from investment, distribution, finance, and operations into AI architecture requirements and roadmaps. Guide the Architecture Review Board (ARB) for AI proposals. Produce executive‑grade artifacts—technology radars, strategic assessments, vendor evaluations, ADRs—to serve as an AI thought leader and trusted advisor.
• Technology Scanning & Innovation: Operate continuous scanning of frontier AI developments and distill insights for senior leadership. Evaluate and pilot emerging AI capabilities with clear proof‑of‑concept criteria. Maintain relationships with AI vendors, cloud hyperscalers, research institutions, and peer firms for benchmarking.
• Team, Collaboration & Community: Mentor architects and engineers on AI design patterns and responsible AI practices. Contribute to Enterprise Architecture practice development, including standards and templates, and represent the firm in external AI forums and industry groups.

Qualifications

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or related fields.
• 10+ years in technology architecture, 3–5 years focused on AI/ML architecture in large, complex enterprise environments.
• Hands‑on command of modern AI stack: LLM APIs and fine‑tuning, vector databases, RAG, embedding pipelines, prompt engineering, and agent orchestration frameworks (LangChain, AutoGen, or equivalents).
• Practical exposure to agentic AI architecture, multi‑agent coordination, and MCP or similar frameworks.
• Experience with enterprise data platforms (Snowflake, Databricks, or comparable) and integrating AI on top of them.
• Strong understanding of cloud‑native architecture on AWS, including AI/ML services such as Bedrock.
• Ability to produce high‑quality architecture artifacts—reference architectures, technology radars, ADRs, capability assessments.
• Familiarity with enterprise architecture frameworks such as TOGAF and operation within Architecture Review Boards.
• Excellent communication skills, synthesizing complex technical topics for non‑technical stakeholders.

Preferred

• Master’s or PhD in Computer Science, AI, ML, Data Science, or related field.
• Experience in financial services (asset management, investment banking, fintech) with knowledge of investment workflows, data governance, and regulatory obligations.
• Knowledge of AI governance frameworks, model risk management guidelines, and emerging AI regulations.
• Familiarity with emerging AI‑adjacent technologies: quantum computing for AI, blockchain/DLT, etc.

Work Flexibility

This role is eligible for hybrid work, with up to three days per week from home.

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