Principal Solution Architect

Avalara

21h

About The Position

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.

Requirements

• B.S. in Computer Science or Engineering (required)
• 10+ years of experience in solution, enterprise, or platform architecture roles
• Strong hands-on experience with modern automation and integration platforms (iPaaS and workflow orchestration tools)
• Experience architecting for platforms such as n8n, Boomi or similar platforms like mulesoft/workato, or comparable automation ecosystems
• Experience designing AI-enabled, API-driven, and event-based architectures for enterprise workflows and transformation initiatives
• Deep understanding of automation patterns, middleware, data transformation, agent orchestration, and human-in-the-loop workflow design
• Strong knowledge of REST, webhooks, OAuth, SSO, API security, and governance best practices for AI-enabled systems
• Experience with cloud-native architectures and AI/ML services (AWS, Azure, or GCP)
• Proven ability to influence enterprise-wide technical direction and partner effectively with AI Automation Engineers, BSAs, and cross-functional leaders
• Demonstrating applied AI impact — not casual familiarity — is required.

Responsibilities

• 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
• Partner across business, platform, data, security, and engineering functions to create shared clarity from concept through execution for transformation initiatives
• Work closely with AI Automation Engineers and BSAs to turn business process opportunities into governed, implementation-ready automation architectures
• Communicate trade-offs, sequencing, and architectural decisions using data, business impact, risk, and cost considerations
• Solve ambiguous, high-complexity challenges spanning workflows, systems, AI agents, process controls, and enterprise change
• Define enterprise standards, reference architectures, documentation templates, and best practices for AI automation and transformation initiatives
• Establish performance, reliability, observability, and cost-management benchmarks for deterministic and AI-enabled workflows
• Reduce automation and architectural debt through proactive platform direction, reusable patterns, and rationalization of fragmented solutions
• Improve resilience, scalability, governance, and long-term maintainability across automation platforms and cross-functional process architectures
• Provide architectural oversight on high-impact AI automation and business transformation initiatives
• Mentor AI Automation Engineers, BSAs, and solution designers, raising overall automation architecture maturity and cross-functional execution quality
• Guide contractor and vendor alignment to enterprise standards for automation, agentic workflows, governance, and platform use
• Elevate organizational AI automation capability through durable architectural principles, reusable patterns, and clear decision frameworks
• Design and govern AI-enabled automation patterns, agentic workflows, and transformation architectures that improve speed, scale, and decision quality
• Evaluate and incorporate AI-driven orchestration, prompt and model governance, and human-in-the-loop decision frameworks into enterprise architecture
• Use AI tools to improve architectural documentation, process analysis, impact assessment, and scenario modeling
• Identify AI opportunities tied to measurable business outcomes (efficiency, cycle-time reduction, reliability, employee experience, customer impact, risk reduction)
• Apply AI responsibly, with attention to governance, security, compliance, auditability, and cost control

Benefits

• Total Rewards
• In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses.
• Health & Wellness
• Benefits vary by location but generally include private medical, life, and disability insurance.
• Inclusive culture and diversity
• Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal