Required Skills & Experience :

Backend (Must-Have) :

- 4 to 6 years of professional experience building scalable backend systems and RESTful APIs using Java (Spring Boot, Spring MVC).

- Strong proficiency in Java ecosystem : Spring Framework (Boot, Security, Data JPA), Maven/Gradle, JUnit, and Hibernate ORM.

- Solid experience with relational databases (PostgreSQL / MySQL) including query optimization, indexing strategies, stored procedures, and migration management.

- Working knowledge of caching (Redis), message queues (RabbitMQ / Kafka), and asynchronous processing patterns.

- Hands-on experience with Docker, CI/CD pipelines (GitHub Actions, Jenkins, or equivalent), and cloud services (AWS preferred).

- Understanding of microservices architecture, API gateway patterns, service discovery, and distributed system fundamentals.

- Strong grasp of authentication and authorization patterns (JWT, OAuth 2.0), middleware design, and API security best practices.

AI & General :

- Demonstrated ability to use AI coding tools (GitHub Copilot, Claude, Cursor, ChatGPT, or equivalent) as part of daily development workflow.

- Ability to critically evaluate, debug, and improve AI-generated code rather than accepting it blindly.

- Strong problem-solving skills with a solid foundation in data structures and algorithms.

- Proficiency with version control (Git) and collaborative branching strategies.

- Excellent written and verbal communication skills.

Nice to Have :

- Experience building backend systems for trading platforms, order book engines, matching engines, or financial data pipelines.

- Familiarity with virtual/digital asset platforms, crypto exchanges, or fintech products.

- Exposure to real-time data handling (WebSockets, Server-Sent Events) in trading or market data contexts.

- Knowledge of RFQ (Request for Quote), OTC, or institutional trading workflows.

- Exposure to FIX Protocol (Financial Information eXchange) development for order routing, trade execution, or market data integration in trading systems.

- Experience with prompt engineering or building AI-augmented features within applications (e.g., AI chat interfaces, intelligent form-fill, copilot-style UX).

- Experience with GraphQL, event-driven architectures, or serverless patterns (AWS Lambda, API Gateway).

- Understanding of security best practices for financial applications (token management, data encryption, secure API communication).

- Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK stack, Datadog).