> Markdown version of [/jobs/ext/1906673-sr-enterprise-ai-data-architect](https://www.wearedevelopers.com/jobs/ext/1906673-sr-enterprise-ai-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Enterprise AI Data Architect - **Company:** T. Rowe Price - **Location:** Baltimore, MD, United States (Remote available) - **Experience:** Expert - **Salary:** $121,000.0 - $206,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Application Frameworks, Application Integration Architecture, Architectural Patterns, ARM Architecture, Cloud Database, Information Systems, Continuous Integration, Data Architecture, Data Security, Software Design Patterns, Python (Programming Language), Machine Learning, Metadata, Software Deployment, Enterprise Data Management, Enterprise Application Integration, Enterprise Software Applications, Data Ingestion, Snowflake, IT Architecture, Generative AI, Information Technology, Data Management, Programming Languages - **Published:** August 3, 2026 - **Apply:** https://www.disabledperson.com/jobs/73968456-sr-enterprise-ai-data-architect ## About the Role We are looking for an experienced architect with a passion for data and a talent for driving technical consensus. We value your background and we place a high emphasis on your ability to continuously learn and master new technologies. The ideal candidate will have: * 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. Preferred: * A Bachelor's or Master's degree in a technical, 5 years of experiences working in Asset Management or a related financial services or highly regulated industry. * AWS certified AI practitioner. SnowPro Core Certification. ## Description As a Senior Enterprise AI Data Architect, you will lead the design, governance, and evolution of enterprise data and AI architecture capabilities across the firm. This role is responsible for defining reference architectures, guiding implementation patterns, and ensuring scalable, secure, and governed solutions that enable enterprise data and AI outcomes. The ideal candidate brings deep expertise in modern cloud data platforms, AI/ML architecture, and enterprise integration patterns, along with strong communication and stakeholder management skills. This is a highly hands-on, full-stack architecture role spanning data ingestion, transformation, semantic and consumption layers, model orchestration, application integration, and production deployment patterns. The role includes both strategic architecture leadership and practical execution, including prototyping and proof-of-concept development to validate new capabilities. We are seeking an energetic, creative, and technically strong architect who enjoys solving complex enterprise problems and building reusable frameworks, standards, and patterns that scale data and AI capabilities across the organization. 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. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The Innovation Formula: Fast Prototyping, Data Analysis, and Real User Insights](https://www.wearedevelopers.com/videos/1421-the-innovation-formula-fast-prototyping-data-analysis-and-real-user-insights) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)