Role Description 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. - Partner across engineering, product, operations, and platform teams to build systems that support Avalara’s long-term AI-first Returns strategy. - Elevate 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. - 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. This role is not eligible for visa sponsorship. Qualifications - 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. Requirements - 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. Benefits - 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.