Senior Software Engineer I – Backend & AI-Enabled

Everbridge

Skills

Design, develop, and maintain scalable, secure, and high-performance backend services using Java and Spring Boot.
Develop and maintain Infrastructure as Code (IaC) using Salt and Terraform to provision, manage, and support AWS infrastructure for SaaS applications.
Build and evolve RESTful APIs, microservices, and event-driven systems that support business-critical workflows.
Collaborate with cross-functional teams, including frontend engineers, to deliver seamless end-to-end product experiences.
Leverage AI-assisted development tools and practices to accelerate coding, testing, debugging, documentation, and code reviews while maintaining high standards of quality and security.
Drive observability, reliability, automation, and operational excellence across services, including monitoring, incident response, troubleshooting, and performance optimization.
Participate in architecture discussions, technical design reviews, and engineering best-practice initiatives.
Support production systems through on-call participation, incident management, and continuous service improvements.
Mentor and support engineers through code reviews, technical guidance, and knowledge-sharing activities.

5+ years of professional software engineering experience building enterprise-grade applications.
Strong expertise in Java and Spring Boot development.
Strong expertise in Infrastructure as Code (IaC), with hands-on experience using Salt and Terraform.
Experience designing and building cloud-native backend systems using RESTful APIs, microservices, Docker, Kubernetes, and related container orchestration technologies.
Strong understanding of distributed systems, scalability, performance, reliability, and secure software design principles.
Experience with cloud platforms such as AWS.
Hands-on experience with CI/CD pipelines, automated testing, and modern DevOps practices.
Experience using AI-powered development tools such as GitHub Copilot, Cursor, Claude Code, Codex, Windsurf, Kiro, or similar platforms.
Ability to critically evaluate, validate, and improve AI-generated code while maintaining quality, security, and maintainability standards.
Interest in continuously learning and applying emerging AI-assisted development practices.
Excellent problem-solving, debugging, and analytical skills.
Experience with observability, monitoring, and production support practices.
Ability to work effectively in Agile/Scrum environments.