- Hands-on practical experience delivering system design, application
development, testing, and operational stability for large-scale, distributed, mission-critical systems
- Advanced in one or more programming language(s) Java 17+ with Spring Boot and
microservices.
- Proficient across SDLC execution, including automation/continuous delivery
practices and agile methods such as CI/CD, application resiliency, and security
- Demonstrated proficiency within a technical discipline (e.g., cloud,
artificial intelligence, machine learning, mobile, etc.) and ability to evaluate current and emerging technologies to recommend future-state solutions
- Experience applying enterprise-authorized AI capabilities within the work
environment in software engineering and architecture workflows with strong validation habits and awareness of data sensitivity.
- Ability to evaluate and integrate AI-enabled capabilities into cloud-native
architectures while meeting resiliency, security, and auditability requirements.
- In-depth knowledge of the financial services industry and their IT systems
- Strong knowledge of architecture patterns such as event-driven and streaming
(Kafka), CQRS, Saga, domain-driven design and API design. Strong data architecture skills, including data modeling, Oracle and complex SQL, NoSQL, and options such as ODS, data lake, data warehouse, OLTP and OLAP
- Practical cloud-native experience with AWS (or equivalent), Docker,