Principal Automation Engineer

PLEASE NOTE

Bitovi has been engaged by Avalara to lead initial and technical interviews for this role. While Bitovi will conduct the early rounds, the final interview and hiring decision will be made by Avalara directly.

Role Summary

As Avalara continues to scale its AI‑first enterprise systems, workflows, and automation footprint, we must ensure our AI automation and transformation architecture is intentional, governed, and built for long‑term scale. This role exists to define and drive enterprise architecture for AI automation and business transformation, reduce fragmentation across workflow, agent, and integration solutions, and enable faster, more reliable delivery of automation initiatives that support business growth and operational excellence.

This is a senior individual contributor lead role responsible for shaping scalable AI automation architectures, improving solution resilience and governance, and ensuring platform strategy supports measurable business outcomes across the company. This role will work extensively with business stakeholders, AI Automation engineers and BSAs to turn business transformation opportunities into durable, enterprise‑grade architectural patterns.

This role directly strengthens Avalara's enterprise AI automation and transformation ecosystem by increasing architectural rigor, scalability, reuse, and long‑term sustainability across business workflows, platforms, and enterprise systems.

• Improve operational efficiency, resilience, and process quality by establishing scalable AI automation architecture standards and governance guardrails
• Accelerate transformation delivery and reduce rework through clear design frameworks, decision models, and reusable automation patterns
• Enhance employee and customer experience by reducing manual work, process fragmentation, and automation risk
• Embed AI‑first architectural practices that improve automation scale, decision quality, and measurable business outcomes

• Holding high standards for architectural clarity, quality, and accountability
• Using data and measurable impact to guide enterprise technical decisions
• Simplifying complex, cross‑system and cross‑workflow challenges into scalable and sustainable designs
• Guiding AI Automation Engineers, BSAs, and solution designers to raise automation maturity and talent density
• Challenging assumptions respectfully and improving execution rigor across teams
• Leaving every system, process, and architectural framework stronger than it was before

• Lead evaluation of AI automation, agentic workflow, and transformation initiatives across the organization
• Define architectural decision frameworks and long‑term platform strategy for n8n, Boomi, APIs, event‑driven orchestration, and AI services to reduce duplication and increase reuse
• Establish governance guardrails for AI‑enabled workflows, agents, prompts, models, data flows, and human‑in‑the‑loop controls to ensure scalability, reliability, auditability, and responsible use
• Anticipate growth, compliance, security, and operational risks across automation platforms and transformation programs before they materialize
• Influence cross‑functional roadmaps with AI Automation Engineers, BSAs, and business leaders based on architectural trade‑offs, platform fit, and measurable outcomes

• Translate enterprise capability needs into clear, implementable technical designs that accelerate AI automation delivery
• Create architectural blueprints for intelligent workflows, agentic process patterns, and cross‑system orchestration that reduce ambiguity and minimize rework
• Design secure, scalable, and resilient automation patterns across SaaS systems, internal platforms, APIs, data ecosystems, and AI/ML services
• Drive API‑first, event‑driven, and human‑in‑the‑loop architecture standards that improve interoperability, control, and long‑term maintainability
• Lead architecture reviews and represent AI automation and transformation strategy in executive and cross‑functional forums