Senior Java Developer - Spring Boot

Job Description :

Responsibilities :

- Design and build scalable, reliable backend systems that power core enterprise platforms.

- Develop and maintain microservices and event-driven architectures, ensuring systems are loosely coupled and highly available.

- Take ownership of end-to-end system development, from design to deployment and production support.

- Ensure systems are production-ready by implementing strong observability, monitoring, and alerting mechanisms.

- Optimise system performance by improving latency, throughput, and resource utilisation.

- Collaborate with cross-functional teams to define APIs, service contracts, and data models.

- Implement resilience patterns such as retries, circuit breakers, and graceful degradation.

- Contribute to and improve CI/CD pipelines and deployment processes for faster and safer releases.

- Write clean, maintainable, and well-tested code, following best engineering practices.

- Use production data and metrics to continuously improve system reliability and performance.

- Participate in code reviews, technical discussions, and architectural decisions.

- Support and mentor team members, contributing to overall engineering excellence.

- Explore opportunities to integrate automation or AI-driven enhancements where applicable.

Requirements :

- Strong expertise in Java (Spring Boot) and working knowledge of Kotlin for building scalable backend services.

- Deep understanding of distributed systems design, including scalability, fault tolerance, and eventual consistency.

- Hands-on experience with microservices architecture and event-driven systems using messaging platforms like Kafka.

- Proficiency in working with both relational databases (PostgreSQL, Oracle) and NoSQL databases (MongoDB, Cassandra, Redis), including data modelling and performance optimisation.

- Experience with API design, service contracts, and building high-throughput, low-latency services.

- Familiarity with cloud-native development in environments like AWS, GCP, or Azure.

- Strong experience in containerization (Docker) and orchestration tools like Kubernetes.

- Knowledge of CI/CD pipelines, automated testing, and deployment strategies (blue-green, canary releases).

- Understanding of observability practices, including logging, monitoring, and distributed tracing.

- Exposure to search technologies like ElasticSearch.

- Solid foundation in data structures, algorithms, and problem-solving.

- Working knowledge of secure coding practices and authentication/authorisation mechanisms.

- Exposure to AI-assisted development tools and a basic understanding of integrating AI-driven components (good to have).

- Leverage AI coding assistants for development and utilise them to generate better quality output.

- Support integration of AI or automation-driven components into the backend systems.

- Ensure AI-enabled components operate within defined reliability and safety boundaries.

- AI exposure is valued, but distributed systems engineering remains the primary focus of this role.