# Avalara — Principal Enterprise Architect

- Generated: 2026-09-10 07:53:51 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4464110652/
- Provider: LinkedIn
- Posted: approximately 2026-09-09 03:53 PM EDT (from '16 hours ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp
- Applicants: 30 applicants
- Work model/location: Remote — United States; corroborated by indexed copies of the exact posting
- Compensation: Geographic base ranges reported up to $306,300; exact Massachusetts range is not disclosed in the LinkedIn text
- Travel: Not disclosed
- Positioning track: Technical IC
- Fit outcome: PASS — 97%

## Direct-match strengths

Enterprise AI standards, reference architectures, governance guardrails, agents, LLMs, orchestration, enterprise integrations, AWS AI/ML, security, privacy, observability, cost controls, build/buy decisions, hands-on prototypes, enablement communities, workshops, executive communication, and production scaling.

## Hard or material gaps

The exact posting names n8n, Boomi, MuleSoft, Workato, or comparable iPaaS/orchestration experience; Keith has strong comparable workflow orchestration, event-driven integration, APIs, and agent frameworks but not those named products. TOGAF is familiar methodology context rather than a mandatory certification. Massachusetts-specific compensation should be confirmed.

## Evidence map

1. 10+ years enterprise/platform architecture (weight 3, evidence 3/3) — 29 years of architecture across enterprise software, AWS, data, AI, and SaaS.
2. Architecture standards and reference patterns (weight 3, evidence 3/3) — Created reusable AWS/AI architectures, standards, accelerators, and global technical guidance.
3. Hands-on LLMs and agent frameworks (weight 3, evidence 3/3) — Direct production LLM, RAG, LangChain/LangGraph, MCP, and multi-agent implementation.
4. AI governance, security, privacy, reliability (weight 3, evidence 3/3) — Direct MassMutual governance/privacy and AssistX production controls.
5. Cloud, data, integrations, distributed systems (weight 3, evidence 3/3) — Deep AWS, API, data, event-driven, microservice, and distributed-system experience.
6. Prototype through production (weight 3, evidence 3/3) — Repeated hands-on concept-to-production delivery.
7. iPaaS/orchestration platforms (weight 2, evidence 2/3) — Strong comparable orchestration, APIs, EventBridge, Step Functions, and agent frameworks; named iPaaS tools are not claimed.
8. Communities, workshops, thought leadership (weight 2, evidence 3/3) — Built 180+ person AWS communities, 170+ assets, and delivered 50+ presentations.
9. Compensation/work model (weight 3, evidence 3/3) — Remote U.S.; indexed geographic ranges reach $306,300.

## Keyword diagnostic

Near-direct alignment with the full mandate: define reusable enterprise AI architecture and governance while personally validating emerging technology and moving pilots into production.

## Full normalized job description

The Opportunity
Avalara is becoming an
AI-first company
, and we’re looking for a
Principal Architect, Enterprise AI
to help define how AI is architected, governed, scaled, and adopted across the enterprise.
This is a senior, hands-on architecture role for someone who combines deep
enterprise/platform architecture expertise
with genuine, current experience building with
AI, LLMs, agent frameworks, and automation technologies
.
You will establish the architecture standards, governance guardrails, decision frameworks, and reusable patterns that enable AI solutions to move successfully from
experimentation and pilots into secure, scalable production systems
. At the same time, you’ll stay close to the rapidly evolving AI landscape—personally testing new models, frameworks, tools, and platform capabilities and translating what matters into practical solutions for Avalara.
What You’ll Do
Define and evolve
enterprise AI architecture standards, reference patterns, design frameworks, and governance guardrails
.
Lead architecture decisions across
AI, data, integrations, cloud infrastructure, identity, security, and enterprise platforms
.
Architect resilient, observable, secure, and cost-aware
AI-enabled workflows and agentic systems
at production scale.
Establish practical decision frameworks for
build vs. buy vs. integrate, model/vendor selection, data access, security, and governance
.
Track and personally evaluate emerging
LLMs, agent frameworks, copilots, orchestration technologies, and AI platform capabilities
across OpenAI, Anthropic, Google, Microsoft, AWS, and the broader AI ecosystem.
Design and build
proof-of-concepts and pilots
against real business use cases, with clear success criteria and a path to production.
Partner with platform, data, security, engineering, and enterprise architecture teams to move validated AI capabilities into scalable production environments.
Work alongside
AI Automation Engineers and Business Systems Analysts
to translate complex business opportunities into governed, implementation-ready architectures.
Lead architecture reviews and communicate technical trade-offs, risk, cost, and business impact to both engineering teams and executive stakeholders.
Create reusable patterns, guidance, demos, and workshops that help teams across Avalara adopt AI effectively and responsibly.
Mentor engineers, architects, and solution designers while raising the overall architectural maturity of Avalara’s AI initiatives.
What We’re Looking For
10+ years of experience
in enterprise, platform, or solution architecture, with experience defining architecture standards, reference patterns, and governance frameworks.
Strong platform-level architecture experience across
integrations, data, cloud infrastructure, security, and distributed enterprise systems
.
Familiarity with enterprise architecture practices such as
TOGAF or equivalent methodologies
, applied pragmatically.
Hands-on experience with modern AI/LLM technologies, APIs, and agent frameworks
—you can prototype and build, not simply evaluate technology from a distance.
Experience designing architectures involving
AI agents, LLM-powered applications, workflow automation, APIs, orchestration, and enterprise integrations
.
Experience with automation/integration platforms such as
n8n, Boomi, MuleSoft, Workato, or comparable iPaaS/orchestration technologies
.
Strong experience with at least one major cloud platform:
AWS, Azure, or GCP
, including AI/ML services.
Demonstrated ability to take emerging technology from
idea → prototype → validated pilot → reusable production architecture
.
Strong judgment around
scalability, reliability, observability, security, data privacy, governance, and cost
.
Ability to communicate complex architecture and emerging AI concepts clearly to technical, business, and executive audiences.
A genuine habit of staying current with—and personally experimenting with—the rapidly changing AI ecosystem.
B.S. in Computer Science, Engineering, or equivalent practical experience.
Nice to Have
Experience leading internal
AI enablement programs, workshops, architecture communities, or communities of practice
.
Public writing, speaking, open-source contributions, or demonstrated thought leadership in applied AI.
What Success Looks Like
You won’t simply design individual AI solutions. You’ll help shape
how Avalara thinks about, governs, architects, and executes AI adoption at enterprise scale
.
Success means creating architectural standards teams actually use, rapidly identifying which emerging AI capabilities matter, turning promising ideas into production-ready patterns, reducing architectural rework, and helping Avalara move faster with AI
without compromising scalability, security, governance, or engineering rigor
.

## Artifact metadata

- Resume: https://bit.ly/4yuN3lh
- Cover letter: https://bit.ly/4r8z0Qe
- Validation: PASS — 2-page resume (947 words), 1-page cover letter (218 words); PDF geometry, bounds, annotations, links, and visual pages verified.
- Google Drive used: No