Principal Architect - Enterprise AI

Bitovi•Durham, NC

4d•Remote

About The Position

As a Principal Architect, Enterprise AI, you will shape how Avalara adopts AI across the enterprise. You will turn new AI capabilities and validated pilots into scalable architecture standards, reusable patterns, decision frameworks, and governance guardrails. This is a senior individual contributor role reporting to the VP of Enterprise AI Transformation. While you will influence teams across the organization, you will not have direct people management responsibilities. You will combine strategic enterprise architecture with hands-on AI exploration. You will stay current with advances in AI, personally test new models, agent frameworks, copilots, and tools, and translate their potential into practical architectural guidance. You will help shorten the path from discovering a new AI capability to using it productively, responsibly, and safely at scale. You will have a full time remote opportunity with Avalara based in the United States of America.

Requirements

Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
10+ years of experience in enterprise, solution, or platform architecture, including architecture standards, reference patterns, and governance frameworks.
Platform architecture experience across integrations, data, cloud infrastructure, APIs, identity, and security.
Hands-on experience building and prototyping with modern AI/LLM tools, APIs, and agent frameworks.
Experience with enterprise architecture frameworks such as TOGAF or equivalent.
Experience with AWS, Azure, or GCP and associated AI/ML services.
Experience guiding teams and executive decision-making.
Experience with AI enablement programs, workshops, or communities of practice.
Experience architecting automation, integration, or orchestration platforms such as n8n, Boomi, MuleSoft, or Workato.
Public writing, speaking, or open-source contributions related to applied AI.

Responsibilities

Define and maintain enterprise architecture standards, reference patterns, and governance guardrails for AI-enabled solutions moving from pilot to production.
Establish decision models for build, buy, or integrate choices; model and vendor selection; data access; security; and responsible AI adoption.
Design scalable architecture patterns for AI-enabled workflows and agentic processes across data, APIs, identity, security, and cloud platforms.
Test new AI models, LLMs, agent frameworks, and tools to inform enterprise adoption.
Design proof-of-concepts, define success criteria, and guide solutions from pilot to production.
Lead architecture reviews and communicate trade-offs, risks, and growth to partners.
Partner with teams to translate needs into governed, implementation-ready solutions.
Ensure teams through demos, workshops, and reusable templates to support safe AI adoption.