Avalara is looking for a Software Engineering Manager to lead distributed engineering teams building scalable, cloud-native SaaS solutions. The role involves driving execution, improving engineering quality, and delivering secure systems that simplify tax compliance for customers.
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
Requirements:
- 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