Sr. Manager, Software Engineering
US-Remote
NA Careers
Req #: 16951
Type: Regular
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Overview: Avalara is looking for a Software Engineering Manager to lead distributed engineering teams building scalable, cloud-native SaaS solutions. You will help drive execution, improve engineering quality and reliability, and help deliver secure, high-performance systems that simplify tax compliance for customers. You will report to the Director of engineering. What the Team Does Our engineering teams build and evolve cloud-native platforms that support tax compliance across large-scale transaction environments. The team focuses on building a platform for our customer experiences and user interfaces with scalable architecture, strong engineering fundamentals, operational excellence, and modern development tools and practices that improve speed, quality, and customer experience. What you will do As a Software Engineering Manager, you will lead multiple Scrum teams across geographies and help create scalable SaaS solutions in a distributed environment. You will partner with cross-functional stakeholders, improve engineering execution, and support architectural and operational decisions that strengthen performance, security, reliability, and delivery predictability. You will also help grow engineering talent, establish development practices, and support adoption of AI-enabled workflows that improve productivity and quality across the software development lifecycle. Responsibilities: * * Lead and develop distributed engineering teams delivering scalable SaaS solutions * Define and execute the technology roadmap for best in class web platform. * Drive predictable, high-quality execution across multiple Scrum teams * Support architectural decisions that improve scalability, performance, security, and cost efficiency * Strengthen CI/CD, automation, and DevOps practices to improve deployment speed and quality * Be an escalation point for production and customer-impacting issues * Partner with Product, UX, Architecture, and other stakeholders to align technical work with our priorities * Hire, coach, and develop engineers * Use metrics to guide decisions and continuous improvement * Strengthen engineering fundamentals across object-oriented design, microservices, APIs, and secure development * Lead adoption of AI-enabled development practices that improve team effectiveness Qualifications: * * Bachelor's degree in Computer Science, Engineering, or a related field * 10+ years of software development experience delivering large-scale production systems * 2+ years of engineering management or equivalent leadership experience leading distributed teams * Experience with front-end and full-stack development using technologies such as React, Angular, TypeScript, Node.js, C#, .NET, and REST APIs * Experience designing and building scalable microservices architectures * Hands-on experience with AWS or another major cloud provider and cloud-native architecture * Experience implementing CI/CD pipelines and DevOps practices using tools such as GitLab, Terraform, and Docker * Experience with scalability, performance optimization, and secure development practices * Experience hiring, coaching, and developing engineers * Demonstrated use of data and metrics to drive measurable improvements * Applied experience using AI to improve engineering outcomes such as speed, quality, scale, or cost efficiency * Experience with a relational database such as MySQL, PostgreSQL, or Oracle This role is expected to raise and continuously advance Avalara's AI engineering capability. The manager must demonstrate deep, hands-on experience applying AI across coding, testing, operations, and engineering workflows to drive measurable improvements in productivity, quality, and delivery speed. This leader will introduce new AI tools, establish best practices, and operationalize AI-driven development, ensuring the team moves beyond basic usage toward meaningful innovation and automation. Success requires actively leveling up the AI capability of the engineering organization, mentoring engineers on applied AI techniques, and identifying strategic opportunities where AI can materially improve engineering outcomes and business impact.
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