Avalara is defining the relationship between tax and tech, having built an industry-leading cloud compliance platform. They process over 54 billion customer API calls and over 6.6 million tax returns annually, with rapid growth aiming to be part of every transaction worldwide. Avalara thrives on innovation and a quirky, optimistic culture that empowers its people. As an AI-first company, Avalara integrates AI into workflows, decision-making, and products, expecting its employees to leverage AI to improve efficiency, contribute solutions, and drive results while continuously learning and sharing AI best practices.

About the Position

Introduction

Avalara is undergoing an AI-first transformation, utilizing agentic systems to revolutionize tax compliance for customers, partners, and employees. This role is crucial for building and scaling the Avalara Avi Agent (AAA), the foundational engineering framework for Aviator and future agentic capabilities. The successful candidate will translate emerging AI patterns into secure, reliable, production-grade systems, enhancing automation, improving customer outcomes, and accelerating agentic solution development.

As an Agentic and Machine Learning Engineer V, you will elevate Avalara's capacity to deliver AI-powered products at an enterprise scale. You will establish reusable platform capabilities, implementation patterns, and operational standards for agentic applications, ultimately improving the reliability, accuracy, security, and scalability of these systems. This role will significantly impact customer experiences, compliance workflows, and AI engineering standards throughout Avalara.

Responsibilities

Design, build, and operate foundational agentic platform capabilities for Aviator, AAA, and other Avalara agentic experiences from prototype to production.
Develop scalable LLM application frameworks, orchestration patterns, tool integrations, and agent workflows to ensure enterprise-grade reliability, observability, security, and maintainability.
Create and refine evaluation methods for agentic outcomes, including quality, accuracy, latency, cost, safety, and task-completion effectiveness.
Translate ambiguous business and product requirements into technical designs, prototypes, production features, and measurable engineering outcomes.
Apply modern software engineering practices (CI/CD, automated testing, code review, documentation, operational readiness) to ensure high-quality delivery.
Collaborate with product, engineering, security, data, and business stakeholders to ensure agentic capabilities effectively address customer and operational needs.
Research, assess, and responsibly apply emerging AI technologies (LLMs, model-context protocols, agent-to-agent patterns, retrieval, evaluation, automation techniques).
Document reusable patterns and implementation guidance to help Avalara engineers build consistently, safely, and efficiently.
Mentor engineers and elevate technical standards through design reviews, code reviews, coaching, and demonstrating high-ownership execution.
Enhance the operational robustness of mature high-availability systems while safely integrating new AI capabilities.

Requirements

B.S. in Computer Science, Engineering, or a closely related technical field.
8+ years of relevant professional experience building, deploying, and operating production software systems, with a strong preference for Python experience.
Hands-on experience building LLM applications, agentic systems, or AI-enabled workflows in production or production-like environments.
Experience with LLMs such as GPT, Claude, Llama, or similar models, including practical understanding of prompting, orchestration, evaluation, and reliability considerations.
Experience with enterprise-scale software design, distributed systems, data structures, design patterns, and high-availability system operations.
Experience working in cloud computing environments such as AWS, Azure, or GCP.
Applied familiarity with modern agentic integration patterns and protocols, such as MCP, A2A, tool use, retrieval, and multi-agent orchestration.
Demonstrated ability to use AI to improve measurable outcomes (speed, quality, automation, insight, customer experience, or scale).
Strong communication, documentation, mentoring, and cross-functional collaboration skills.

Benefits

Total Rewards: Competitive compensation package, paid time off, and paid parental leave. Many 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, integrated into business practices and organizational culture. Features 8 employee-run resource groups with senior leadership and executive sponsorship.