Software Engineer (Java Backend – Distributed Systems & High-Performance Platforms)

Job Description

We are seeking a highly capable Software Engineer (Java Backend) to architect, develop, and optimize large-scale distributed backend systems supporting enterprise financial SaaS platforms and high-throughput computational workflows.

This role requires strong expertise in Java internals, concurrent programming, distributed scheduling strategies, and performance optimization in data-intensive environments. The successful candidate will contribute to system architecture enhancement, workflow orchestration design, and reliability engineering in mission-critical production systems.

Key Responsibilities

• Design and implement scalable, high-availability backend services using Java within distributed system architectures.
• Architect and optimize multi-stage workflow orchestration pipelines for computational job execution.
• Develop asynchronous processing mechanisms to reduce critical path latency and improve throughput.
• Design and implement distributed caching strategies, including dataset preloading, eviction policies, and cache consistency controls.
• Optimize scheduling strategies to minimize remote invocation overhead and improve node-level computational efficiency.
• Implement distributed locking mechanisms and concurrency control to ensure data integrity.
• Enhance system fault-tolerance and resilience for large-scale job execution environments.
• Develop diagnostic, replay, and conditional job-dumping frameworks to improve exception analysis and issue reproduction efficiency.
• Conduct performance profiling, JVM tuning, and memory optimization in production environments.
• Collaborate with cross-functional teams to align system architecture with evolving technical and business requirements.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related discipline.
• Minimum 3 years of relevant experience in Java backend development within distributed systems.
• Strong foundation in data structures and algorithms.
• In-depth understanding of:

(i) Java Collection Framework (e.g., HashMap,
Concurrent HashMap) and internal implementation
principles.
(ii) Java concurrency model, lock mechanisms,
synchronization strategies, and thread pool design.
(iii) JVM memory management and performance tuning
concepts.
(iv) Hands-on experience with Redis, including data
structures and persistence mechanisms.
(v) Experience in distributed workflow scheduling
systems.
(vi) Strong analytical and problem-solving skills.

Preferred Qualifications

• Experience in financial systems, enterprise SaaS platforms, or high-performance computing environments.
• Experience optimizing distributed cache architecture and workflow scheduling.
• Experience designing debugging, replay, or exception diagnosis frameworks.
• Familiarity with advanced cache eviction strategies and task execution ordering optimization.

EA Number: 11C4879