Overview

What You’ll Do
Role Summary

As Avalara scales its AI‑first enterprise systems, workflows, and automation footprint, we must reimagine how work is automated, orchestrated, and continuously improved across every function. This role exists to establish and engineer an enterprise‑grade AI automation and transformation ecosystem, with n8n as a core platform, enabling faster process transformation, intelligent workflow execution, and measurable gains in productivity, quality, and operational scale.

This is a high‑impact individual contributor role responsible for elevating automation standards, reducing manual work and process friction, and enabling AI‑powered transformation across the organization.

How This Role Elevates Avalara

This role strengthens Avalara’s enterprise automation and transformation capability by establishing scalable, secure, and measurable AI orchestration standards across the organization.

This AI Automation Engineer will:

Improve operational efficiency and process quality by engineering resilient AI automation solutions and governed platform standards

Accelerate business transformation and reduce cycle time through reusable automation patterns, CI/CD enablement, and standardized development frameworks

Enhance employee and customer experience by removing manual bottlenecks, reducing process defects, and increasing AI workflow intelligence

Advance Avalara’s AI‑first execution model by embedding agentic automation, intelligent decisioning, and data‑driven observability into enterprise workflows

Bar Raiser Expectations

As a Bar Raiser, this role is expected to elevate the capability and execution rigor of the entire automation and transformation function, not simply contribute as a senior engineer. This includes:

Holding high standards for quality, ownership, reliability, and accountability

Using metrics (automation adoption, cycle‑time reduction, SLAs, SLOs, MTTR, cost per workflow) to guide platform and architectural decisions

Simplifying complex business processes into scalable, governed, and maintainable automations

Mentoring engineers and contractors to raise automation maturity and talent density

Challenging technical assumptions constructively and driving measurable improvement

Leaving every platform, process, and engineering practice stronger than it was before

This role does not only build automation, it transforms how work is engineered, automated, governed, and scaled across Avalara.

What Your Responsibilities Will Be
Enterprise AI Automation Leadership

Own the enterprise‑wide AI automation and transformation strategy with n8n as a core orchestration platform

Architect scalable, secure, and resilient automation solutions that eliminate manual effort, improve process quality, and reduce operational friction

Design hybrid patterns leveraging n8n/Boomi, APIs, event‑driven systems, and AI agents to improve reuse, enable intelligent decisioning, and reduce time‑to‑value

Define patterns for embedding AI‑driven workflows (LLMs, agents, and decision engines) into business processes across functions

Lead architecture reviews and drive best‑in‑class automation design standards, including AI‑assisted design patterns and governance

Platform Ownership (n8n)

Serve as a technical owner for n8n and AI workflow automation initiatives

Define environment strategy (dev/test/prod), CI/CD pipelines, and governance models to reduce deployment risk and increase release velocity

Enable AI‑powered workflow capabilities within n8n (e.g., agent orchestration, prompt management, model integrations, human‑in‑the‑loop controls)

Implement workflow standards, logging, monitoring, and reliability guardrails to improve MTTR, uptime, and automation trust

Incorporate AI‑assisted monitoring, anomaly detection, and intelligent alerting to proactively detect failures, drift, and degraded workflow performance

Ensure platform scalability, fault tolerance, and high availability for both deterministic and AI‑driven workflows

Standards & Governance

Establish enterprise automation development standards and best practices

Define exception‑handling frameworks, retry strategies, naming conventions, security protocols, and approval patterns that reduce production defects

Create reusable templates, accelerators, and automation design patterns, including AI agent templates and reusable prompt frameworks

Define governance for AI usage (model selection, cost controls, prompt/version management, data privacy, and auditability)

Introduce code review processes and quality gates that increase execution rigor, including AI workflow validation and evaluation standards

Technical Mentorship & Delivery Excellence

Operate as a player‑coach – hands‑on while mentoring engineers

Guide contractor and external implementation teams to ensure quality and standards adherence

Lead technical design sessions, workflow reviews, and post‑incident reviews

Mentor teams on designing, building, and operationalizing AI agents and autonomous workflows within business processes

Promote best practices for prompt engineering, agent orchestration, human‑in‑the‑loop workflows, and responsible AI automation

Elevate automation engineering capability across the organization, including AI fluency and adoption

12‑Month Success Signals

Enabled AI‑native automation capabilities, including production‑grade AI agents integrated into core workflows

Improved automation reliability and reduced workflow failure rates and/or MTTR

Standardized automation patterns, including AI‑enabled orchestration patterns, adopted across new transformation initiatives

Implemented measurable observability, including AI performance, business impact, and cost metrics

Delivered AI‑driven automation use cases that reduce manual effort, improve decision‑making, or shorten process cycle time across multiple functions

Raised execution standards across the automation team through mentorship, technical leadership, and AI capability development

What You’ll Need To Be Successful
AI Expectations

As an AI‑first company, Avalara expects this role to embed AI into how automation and transformation work is designed and executed. This role will:

Design and implement AI‑enabled workflows and transformation patterns that materially improve speed, automation, and scale

Use AI tools to optimize development productivity, workflow diagnostics, process analysis, and root‑cause investigation

Identify high‑value AI automation opportunities tied to efficiency, reliability, employee experience, or customer impact

Apply AI responsibly with appropriate governance, security, and risk considerations

Elevate AI capability across the automation team by sharing best practices and driving measurable adoption

This role must demonstrate applied AI impact—not casual tool usage—and quantify improvements enabled by AI‑driven automation and transformation.

What You Bring

B.S. in Computer Science, Engineering, or a related field (required)

10+ years of experience in enterprise automation, workflow engineering, integration engineering, or platform architecture

Deep hands‑on expertise in n8n or Boomi, including building and orchestrating AI‑enabled workflows, agents, and cross‑functional business automations

Experience designing API‑first and event‑driven architectures, including integration of AI/ML services and agent‑based systems

Strong understanding of REST, webhooks, OAuth, JWT, and API security, along with secure integration of AI services and model endpoints

Experience implementing CI/CD for automation or integration platforms, including deployment and versioning strategies for AI workflows, prompts, and models

Cloud experience (AWS, Azure, or GCP), including AI/ML services (e.g., Bedrock, Azure OpenAI) and scalable model integration patterns

Familiarity with LLMs, prompt engineering, AI agents, and orchestration frameworks, and how they apply to enterprise automation

Experience with observability and monitoring, including AI‑specific considerations (latency, cost, accuracy, drift)

Proven ability to influence architecture and technical direction at scale, including driving adoption of AI‑powered automation, process transformation, and intelligent orchestration patterns

Avalara is an AI‑first Company
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.

How We’ll Take Care Of You
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.

We’re An Equal Opportunity Employer
Supporting diversity and inclusion is a cornerstone of our company — we don’t want people to fit into our culture, but to enrich it. All qualified candidates will receive consideration for employment without regard to race, color, creed, religion, age, gender, national orientation, disability, sexual orientation, US Veteran status, or any other factor protected by law. If you require any reasonable adjustments during the recruitment process, please let us know.

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