Senior AI Applied Software Engineer

At Backbase, we build AI-powered, secure, enterprise-grade digital banking software used daily by millions worldwide. With seamless integration, unified data, agentic AI, and a complete banking suite built for every line of business, you'll be building the next generation of banking.

The Role

We are seeking a Senior AI applied software Engineer strong backend software engineering experience to own the health of our production systems by resolving complex escalations and driving automation. Our core backend relies heavily on Java, Spring Boot, and microservices orchestrated via Kubernetes.

In this role, we embrace a T-shaped engineering profile. You will anchor your work in your deep expertise of the Java ecosystem, while utilizing AI tools to operate across the wider tech stack.

Rather than just closing tickets, you will use AI and agentic workflows as force multipliers to optimize our support processes, automate repetitive triage tasks, and permanently resolve underlying system defects. You will serve as a technical authority who mentors peers and raises the bar on how we handle application support in a modern, cloud-native environment.

Key Responsibilities

End-to-End Troubleshooting: Take ownership of complex escalations by debugging Java and Spring Boot code, tracing issues through REST APIs, and resolving bottlenecks in our microservices architecture.
AI-Driven Automation: Lead the adoption of agentic tooling, LLMs, and AI automation to streamline incident triage, log analysis, and repetitive support workflows as you identify system pain points.
Infrastructure Navigation: Monitor, debug, and maintain application stability within a Kubernetes-orchestrated containerized environment.
Technical Authority: Act as the highest escalation point and go-to resource for your peers. Review root cause analyses critically and mentor the team on modern, AI-native support practices.
Strategic Problem Solving: Identify trends in system failures, lead cross-system investigations, and plan major code refactoring or automation initiatives to prevent recurrence.
Quality Excellence: Balance rapid incident response speeds with long-term system maintainability, championing performance and reliability standards.

Experience: 5 to 8 years of strong backend engineering expertise and application support.

Core Stack Mastery: Deep, hands-on programming and debugging expertise with Java and the Spring Boot framework.

Architecture & Infrastructure: Extensive experience building or troubleshooting RESTful APIs, microservices architectures, and Kubernetes clusters in production.

Operational Readiness: Willingness and ability to participate in an on-call rotation and respond to out-of-hours emergencies as part of a global "follow the sun" model.

AI Tooling: Demonstrated experience (or strong aptitude and interest) in utilizing AI-driven tools (e.g., AI coding assistants, automated log analyzers, LLM-driven scripting) to optimize workflows and automate operational tasks.

Core Competencies: You are a sound technical judge. You can anticipate how a bug fix will impact a distributed system and communicate architectural trade-offs clearly to both technical and non-technical stakeholders.