Principal AI Platform & Solutions Architect

About the role

The Principal AI Platform and Solutions Architect will lead the transformation of our Enterprise Data Platform (EDP) from a traditional reporting platform into an AI-enabled data platform. This is a hands-on, execution-focused role for someone who can design solution architecture and build production capabilities, starting with a governed MCP Server over our data platform and an AI-enabled, self-serve chat experience for the business.

Responsibilities

• Design and build a governed AI-to-data integration patterns (such as Skills, Agents, and MCP Server) over the Enterprise Data Platform that lets approved AI agents and copilots securely query and act on enterprise data, replacing one-off integrations built per use case.
• Lead solution architecture and hands-on delivery of AI-enabled, self-service data experiences that allow users to interact with enterprise data through natural language.
• Translate AI and GenAI opportunities into production-ready architecture with clear implementation patterns and governance controls while prioritizing high-value, low-effort wins first.
• Build the foundational architecture capabilities including metadata layers, governed semantic models, orchestration workflows, and secure access patterns that support LLM and agent-based use cases.
• Partner with AI capabilities across the organization to reuse existing patterns.
• Serve as the hands-on technical lead for the team's AWS-native platform architecture, owning design decisions and directly contributing to implementation.
• Continuously modernize data pipelines to reduce redundancy, control cost, and improve reliability and observability.
• Codify reusable architecture patterns and mentor data engineers to scale successful patterns across initiatives/projects.
• Serve as the solution architecture contributor in architecture review processes.

Requirements

• Experience delivering reliable, scalable, and cost-effective production data platforms in a data engineering, solution architecture, or platform engineering capacity.
• Experience designing solutions using AWS technologies such as Glue, S3, Redshift, Lambda, Step Functions, and IAM roles and policies.
• Experience applying GenAI/LLM patterns over enterprise data.
• Experience applying the following fundamentals as a solution architect: RBAC, data lineage, DR/HA, modular design, cost optimization.

Qualifications

• Experience implementing the Model Context Protocol (MCP) or comparable patterns for governed AI-to-data integrations.
• Experience with modern data Lakehouse architecture patterns.
• Experience partnering with IT Security teams on IAM and secure data access pattern initiatives.
• Experience mentoring data engineers and establishing reusable architecture standards/patterns that scale across teams.