We are seeking a motivated Full Stack Java Developer with 3-7 years of software development experience and practical familiarity with Java, Spring Boot, React, cloud platforms and microservices. The successful candidate will develop secure, scalable enterprise applications and collaborate with architects, analysts, DevOps engineers and product teams across the software delivery lifecycle.
Lead and deliver technical implementation of Temenos TAP (Triple A Plus) solutions across client projects.
Develop and customize TAP modules, including GUI/WUI development, UDF creation, formats, screen design, and system configuration (parameters, lists, classifications, strategies).
Design and implement WTX maps for data integration and processing....
Taking an active role in team delivery of product and engineering goals.
Delivering high-quality, maintainable, and reusable software systems.
Making technical contributions, and providing technical leadership to software engineers by coaching and mentoring through engineering best practices....
Lead the end-to-end architecture, design and development of embedded software, firmware and application-level solutions for complex, high-performance products.
Define scalable, secure and maintainable software architectures, system interfaces and integration strategies across hardware and software platforms.
Design and develop embedded Linux solutions, including OS customization, kernel configuration, Yocto/ PetaLinux, firmware and application software....
Develop backend services for AI features: Build and maintain scalable APIs and microservices in Java (Spring Boot) or Python that expose our generative AI capabilities - routing user queries to LLMs and other models, processing data, and returning results securely and efficiently.
Integrate generative AI technologies: Partner with data science and ML engineering to productionise models - wrapping them in reliable service interfaces, managing input/output formats, adding supporting data flows such as external API calls and response caching, and ensuring they scale.
Ensure performance and reliability: Own the quality of the services you build through unit and integration tests, profiling and removing bottlenecks, and monitoring and alerting (CloudWatch, Prometheus). Troubleshoot production issues and keep improving logging and observability....
Design, build, and operate production-grade AI and ML services, APIs, libraries, and reusable platform components.
Own end-to-end AI engineering workflows, including data preparation, model integration, evaluation, deployment, monitoring, and continuous improvement.
Support cloud migration efforts, transitioning on-premises data workflows to cloud-based platforms such as Databricks, Cloudera, Amazon AWS, etc....