Software Engineer III, Java / Data

What you'll do

• Design, develop, and deliver secure production code for distributed microservices.
• Make and defend architectural decisions balancing delivery speed with long-term maintainability and cost.
• Use enterprise-authorized AI coding tools to generate, refactor, and test complex deliverables.
• Build reliability into software by instrumenting services with telemetry and designing for failure.
• Engineer automation and self-healing workflows to eliminate manual operational toil.
• Lead incident triage, perform root-cause analysis, and implement permanent fixes for recurring defects.
• Develop and maintain infrastructure-as-code to automate provisioning across AWS environments.
• Mentor engineers and promote the reuse of patterns to improve team engineering practices.

What we're looking for

• Formal training or certification on software engineering concepts and 3+ years of applied experience.
• Advanced, hands-on proficiency in Java and the Spring ecosystem for building RESTful microservices and object-oriented designs.
• Strong experience engineering and operating production workloads on AWS, including EKS, ECS, Lambda, API Gateway, RDS, and CloudWatch.
• Hands-on experience using enterprise-authorized AI-assisted software development tools to generate, validate, and refine code and documentation.
• Understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling of inputs and outputs.
• Strong experience with containerization and orchestration using Docker and Kubernetes.
• Practical experience with NoSQL and/or relational databases at production scale.
• Depth in the full software development lifecycle, including CI/CD, automated testing, code review, and secure coding practices.
• Fluency with CI/CD tooling like Jenkins, build tools like Maven/Gradle, and source control like Git.
• Working knowledge of observability tooling such as Dynatrace, Splunk, or OpenTelemetry/Grafana/Prometheus.
• Experience with event-streaming technologies like Kafka and event-driven architectures (preferred).
• Familiarity with reliability engineering practices including SLIs/SLOs, error budgets, and disaster recovery (preferred).
• Knowledge of the financial services industry and its regulatory and control requirements (preferred).