Senior Enterprise AI Data Architect — Hybrid/Remote

T. Rowe Price; Baltimore (MD); Hybrid; USD 120,000 - 258,000; Full time

Benefits offered by this job

Hybrid work schedule

Annual bonus eligibility

Health and wellness benefits

Paid time off

Fertility and adoption benefits

Job summary

T. Rowe Price is seeking a Senior Enterprise AI Data Architect to lead design, governance, and evolution of enterprise data and AI architecture. The role covers reference architectures, scalable solutions, and hands-on implementation across ingestion, transformation, model orchestration, and deployment.

Strong cloud, AI/ML, and enterprise integration experience are essential. The ideal candidate excels in collaboration, stakeholder management, and delivering production-grade data and AI

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
• 8+ years of experience in data, platform, or solution architecture, including experience designing and delivering enterprise-scale cloud data and AI solutions.
• Hands-on experience with generative AI, machine learning, or advanced analytics solutions, including at least one use case delivered end-to-end into production.
• Strong experience with AWS and Snowflake, including architecture and implementation patterns for governed data access, analytics, and AI integration; experience with Amazon Bedrock Agent Core and Snowflake Cortex strongly preferred.
• Deep understanding of modern data architecture, including data ingestion, transformation, semantic modeling, metadata, lineage, data quality, governance, and production deployment patterns.
• Strong technical skills in Python or another modern programming language, along with experience in APIs, orchestration patterns, CI/CD, infrastructure as code, and operational best practices.
• Strong communication and stakeholder management skills, with the ability to influence architecture decisions, work across technical and business teams, and operate effectively in a fast-evolving environment.

Responsibilities

• Lead the architecture, design, and selective hands-on implementation of enterprise data and AI solutions from concept through production.
• Define end-to-end architecture patterns covering data ingestion, transformation, semantic modeling, retrieval, model orchestration, inference, integration, and deployment.
• Build prototypes and proof-of-concepts to validate architecture decisions, evaluate emerging technologies, and accelerate adoption of new data and AI capabilities.
• Establish reusable design patterns for agentic, analytical, and model-driven workflows using cloud-native and enterprise data platforms.
• Design and guide integration of AI capabilities with enterprise applications, APIs, and data platforms such as Snowflake.
• Partner with engineering teams to ensure architecture patterns are implemented in a scalable, secure, and supportable manner.
• Define standards for metadata, lineage, governance, observability, and lifecycle management across data and AI solutions.
• Evaluate tradeoffs across tools, models, platforms, and integration approaches, and recommend solutions aligned to enterprise strategy and business needs.
• Collaborate with cross-functional teams to align architecture, platform capabilities, and delivery roadmaps.
• Drive adoption of enterprise architecture standards, reusable frameworks, and best practices across data and AI initiatives.

Skills

Data architecture

Cloud data platforms

Python

AWS

Snowflake

AI/ML

CI/CD

APIs

Stakeholder management

Education

Bachelor’s degree in Computer Science or related field

Bachelor’s or Master’s degree in technical field

Tools

Amazon Bedrock Agent Core

Snowflake Cortex

Job description

T. Rowe Price is seeking a Senior Enterprise AI Data Architect to lead design, governance, and evolution of enterprise data and AI architecture. The role covers reference architectures, scalable solutions, and hands-on implementation across ingestion, transformation, model orchestration, and deployment.

Strong cloud, AI/ML, and enterprise integration experience are essential. The ideal candidate excels in collaboration, stakeholder management, and delivering production-grade data and AI