Senior Software Engineer

What You’ll Do

Avalara is an AI-first company. Every engineer is expected to apply AI to improve speed, quality, automation, customer outcomes, and operational scale. AI is embedded into how we build products, operate services, and deliver customer value. Success at Avalara requires using AI as a core engineering capability — not an optional tool.

As a Software Development Engineer, Backend on the Returns team, you will help modernize and scale Avalara’s Returns-as-a-Service (RaaS) ingestion platform that powers tax return preparation, filing workflows, and emerging AI-driven Returns experiences. This role exists to accelerate Avalara’s ability to ingest, validate, normalize, and operationalize increasingly complex tax data at scale while improving reliability, automation, and customer trust.

You will design and deliver scalable backend systems, APIs, ingestion pipelines, and operational tooling that improve filing accuracy, reduce operational friction, and enable faster onboarding of new data sources and filing capabilities. You will partner across engineering, product, operations, and platform teams to build systems that support Avalara’s long-term AI-first Returns strategy.

This role elevates Avalara by improving platform scalability, operational efficiency, and customer outcomes while helping establish engineering and AI practices that raise the performance of the broader organization. Successful candidates will demonstrate Bar Raiser behaviors through strong ownership, engineering rigor, customer focus, and continuous improvement of systems, processes, and team capability.

You will report to the Director of Engineering, Returns-as-a-Service Framework.

This is a remote opportunity. #LI-Remote

This role is not eligible for visa sponsorship.

• Design, build, and operate scalable ingestion services that process and validate large-scale tax and returns data with high reliability, accuracy, and operational transparency.
• Improve platform scalability, resiliency, and operational performance by reducing defects, strengthening observability, and improving monitoring and troubleshooting workflows.
• Accelerate onboarding of new ingestion workflows and external data sources while improving SLA attainment, processing quality, and customer outcomes.
• Contribute to architecture decisions, API design, secure-by-design engineering practices, automation strategies, and operational tooling that simplify complexity and improve long-term maintainability.
• Apply AI-assisted engineering practices across software development, testing, operational analysis, documentation, troubleshooting, and workflow automation to improve engineering velocity and quality.
• Identify opportunities to use AI to improve ingestion validation, anomaly detection, operational intelligence, and automated issue resolution at scale.
• Partner cross-functionally with Returns, platform, operations, and product teams to deliver automation capabilities that improve filing accuracy, customer experience, and downstream Returns workflows.
• Raise engineering standards through mentorship, technical leadership, code quality improvements, and reduction of technical debt.
• Demonstrate Bar Raiser behaviors by improving systems, processes, execution quality, and the capabilities of those around you.
• Contribute to measurable business outcomes including improved operational efficiency, reduced processing failures, faster onboarding of filing capabilities, and increased customer trust in Returns processing.

• Reduced ingestion-related operational defects and improved platform reliability metrics.
• Accelerated onboarding timelines for new ingestion workflows and tax data sources.
• Improved observability and operational troubleshooting efficiency across ingestion services.
• Increased automation coverage across validation, monitoring, and operational workflows.
• Demonstrated measurable engineering productivity improvements through effective AI-assisted development practices.
• Positively influenced team engineering standards, code quality, and operational rigor through mentorship and technical leadership.

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