What You'll Do

Avalara's Content Engineering platform supports the compliance content that helps customers manage complex obligations across jurisdictions and product lines. Avalara is modernizing the compliance content lifecycle by building agentic scalable, reliable, cloud-native systems that make it faster and easier to onboard, validate, enrich, and deliver new content types.

This role exists to lead the design and delivery of enterprise-grade agentic applications and machine learning systems that integrate into Avalara's products, platforms, and internal workflows. The Machine Learning Engineer V owns complex AI systems from architecture through production, including full-stack application integration, backend services, agent orchestration, model and agent evaluation, deployment, observability, support, and ongoing improvement.

This is not a pure machine learning operations role. This role requires a senior engineer who builds agentic systems, integrates them with mainstream applications, applies sound software development life cycle practices, and operates production AI capabilities as secure, reliable, scalable product systems. This role sits within Content Engineering team and you will be reporting to Senior Manager, ML Engineering. This is a role.

What Your Responsibilities Will Be

Lead the architecture and delivery of enterprise-grade agentic applications that integrate with Avalara products, Content Engineering platforms, services, workflows, and user experiences.
Build end-to-end AI-enabled systems that include backend services, application programming interfaces, data access patterns, agent orchestration, retrieval, tool integration, user-facing application components, evaluation, deployment, monitoring, and production support.
Design reusable platform capabilities and cloud-native services that support new compliance content types and improve the compliance content lifecycle.
Make architecture decisions that improve scalability, reliability, resiliency, observability, maintainability, security, and operational efficiency.
Operationalize AI capabilities using modern orchestration and agentic frameworks to improve automation, accuracy, delivery speed, and system quality.
Integrate agents with enterprise applications, data sources, workflow systems, and cloud-native services while maintaining secure and maintainable system boundaries.
Establish engineering standards for software design, code quality, continuous integration and delivery, automated testing, deployment automation, observability, incident response, and production operations.
Improve platform performance, latency, throughput, reliability, and cost efficiency at scale.
Apply evaluation, monitoring, and deployment practices that improve AI-enabled system performance in production.
Work across model providers and model families to improve model selection, routing, quality, latency, reliability, and spend.
Partner with engineering, infrastructure, product, security, data, and domain teams to deliver measurable customer and business outcomes.
Mentor engineers, lead design reviews, create reusable engineering patterns, and raise team capability in distributed systems, cloud engineering, software architecture, full-stack development, and responsible AI adoption.

What You'll Need To Be Successful

B.S. in Computer Science or Engineering.
12+ years of experience in software engineering, machine learning engineering, applied machine learning, generative AI, enterprise application development, or production AI systems.
Experience building scalable, distributed production systems using cloud-native architecture and at least one major cloud platform, such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
Experience building enterprise agentic applications that use large language models, tools, workflows, retrieval, application programming interfaces, and application integration patterns.
Experience integrating AI capabilities into production applications, backend services, user workflows, developer platforms, or enterprise systems.
Strong software engineering skills in Python and experience designing backend services, application programming interfaces, distributed systems, and cloud-native platforms.
Full-stack engineering experience across backend services, application programming interfaces, relational databases, scalable data access patterns, frontend-backend contracts, authentication, and modern web technologies.
Experience applying the software development life cycle end to end, including requirements analysis, architecture, design, implementation, testing, release planning, deployment, monitoring, incident response, support, and continuous improvement.
Experience shipping and supporting production machine learning, large language model, or AI-enabled application systems beyond experimentation or research prototypes.
Hands-on experience with retrieval-augmented generation, embeddings, prompt design, evaluation, classification, agent tool-use patterns, small language models, or large language model-powered workflows.
Experience with cloud-native systems, asynchronous or distributed workflows, observability, monitoring, deployment automation, and production operations.
Ability to design for security, access control, governance, compliance, reliability, maintainability, resiliency, and cost efficiency.
Strong system design skills and ability to lead technically complex initiatives across multiple stakeholders.
Ability to mentor engineers, lead design reviews, and raise technical standards across teams.

Avalara is an AI-first Company

AI is embedded in our workflows, decision-making, and products. Success here requires embracing AI as an essential capability.

You'll bring experience using AI and AI-related technologies, ready to thrive here.
You'll apply AI every day to business challenges - improving efficiency, contributing solutions, and driving results for your team, our company, and our customers.
You'll grow with AI by staying curious about new trends and best practices, and by sharing what you learn so others can benefit too.

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.

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 You Need To Know About Avalara

We're defining the relationship between tax and tech.

We've already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we're a billion dollar business - and we're not slowing down until we've achieved our mission - to be part of every transaction in the world.

We're bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we've designed, that empowers our people to win. We've been different from day one. Join us, and your career will be too.

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.