Senior Software Engineer

Avalara is an AI-first company seeking a Senior Software Engineer to modernize and scale their Returns-as-a-Service ingestion platform. The role involves designing and delivering scalable backend systems and APIs while applying AI to improve operational efficiency and customer outcomes.

Responsibilities:

• 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

Requirements:

• B.S. in Computer Science or Engineering
• 5+ years of relevant experience designing, building, and operating production-grade backend systems and distributed platforms
• Experience building scalable APIs, ingestion pipelines, data processing systems, and cloud-native services in modern engineering environments
• Strong experience with C#/.NET and modern software engineering practices including CI/CD, automated testing, secure development, and reliability engineering
• Experience operating workloads in AWS, including networking, IAM, observability, security, and cloud operational best practices
• Demonstrated ability to improve operational excellence through monitoring, troubleshooting, automation, scalability, and defect reduction initiatives
• Hands-on experience applying AI-assisted development tools and workflows to improve engineering speed, quality, automation, or operational effectiveness
• Experience integrating with or leveraging generative AI technologies such as OpenAI, Bedrock, Vertex, or Hugging Face, including practical understanding of prompt design, token optimization, rate limits, and retrieval-based patterns
• Strong ownership mindset with the ability to simplify complex systems, drive measurable outcomes, and improve the performance of teams and platforms over time
• Ability to demonstrate applied AI impact through measurable examples tied to engineering efficiency, automation, customer experience, quality improvement, or operational scale
• Demonstrated track record of using AI to drive measurable improvements in engineering productivity, software quality, operational efficiency, customer outcomes, or platform scalability
• Hands-on experience leveraging AI-assisted development tools and workflows across coding, testing, debugging, documentation, code review, operational analysis, and automation
• Experience integrating with or leveraging generative AI technologies such as OpenAI, Bedrock, Vertex, or Hugging Face, including practical understanding of prompt engineering, token optimization, rate limiting, evaluation approaches, and retrieval-augmented generation (RAG) patterns
• Ability to identify and implement AI-driven opportunities that reduce manual effort, accelerate delivery, improve data quality, strengthen operational intelligence, or enhance customer experiences
• Demonstrated judgment in applying AI responsibly, including awareness of data privacy, security, governance, reliability, and accuracy considerations in production systems
• Ability to quantify AI impact through measurable business or engineering outcomes such as reduced operational costs, faster issue resolution, improved development velocity, increased automation coverage, or higher platform reliability
• Proven ability to elevate the AI capabilities of peers and teams through mentorship, knowledge sharing, experimentation, and establishment of scalable AI engineering best practices
• Strong ownership mindset with the ability to simplify complex systems, drive measurable business outcomes, and consistently raise engineering standards across teams and platforms
• Demonstrated Bar Raiser behaviors through high accountability, strong technical judgment, continuous improvement, and a track record of leaving systems, processes, and teams stronger than they were found