Celoxis- Medior Backend Java Developer
Job Description
Medior Backend Java Developer
\nAbout the Project
\nJoin our team and work on a mature, feature-rich Project & Service Automation (PSA)
\nplatform, an enterprise-grade solution that powers project management, resource planning,
\ntime tracking, expense management, and business reporting for global customers. Our
\nplatform supports multi-tenant environments with complex business workflows, and we are
\nactively expanding its capabilities with advanced AI/ML features.
\nKey Responsibilities
\n%CF; Design and implement RESTful APIs following established architectural pattern
\n%CF; Develop and maintain backend features for project management, resource allocation,
\ntime tracking, and expense management modules.
\n%CF; Participate in AI/ML feature development using LangChain4j and Spring AI
\nframeworks
\n%CF; Work with ORM to build complex database queries and optimize data access layers
\n%CF; Implement business logic for approval workflows and process automation
\n%CF; Integrate third-party services (accounting systems, CRM platforms, authentication
\nproviders)
\n%CF; Develop scheduled background, data synchronization, and forecasting
\n%CF; Ensure proper security implementation through ACL and role based access control
\nRequired Technical Skills
\nTechnologies & Frameworks
\n%CF; Backend: Spring Boot 3.x, Spring MVC, Spring AOP, Spring WebSocket
\n%CF; ORM: Apache Torque with Criteria-based query building
\n%CF; Database: PostgreSQL with pgvector for AI embeddings
\n%CF; Security: OneLogin SAML, Google Authenticator, jBCrypt
\n%CF; Integrations: QuickBooks SDK, Zapier, Google services, MPXJ
\nArchitecture & Design Patterns
\n%CF; Service Layer Pattern and Repository Pattern
\n%CF; Singleton, Factory, and Decorator patterns
\n%CF; Event-driven architecture (pub/sub, event listeners)
\n%CF; Multi-layered architecture design
\n%CF; Understanding of domain-driven design principles
\nDatabase & Data Management
\n%CF; PostgreSQL or similar relational databases
\n%CF; Transaction management and data integrity
\n%CF; Query optimization and performance tuning
\n%CF; Database migration and schema management
\n%CF; Experience with Criteria based query builder
\nExperience Level
\n5+ years of professional Java backend development experience with:
\n%CF; At least 2 years working with Spring Framework
\n%CF; Experience with enterprise-level applications
\n%CF; Understanding of multi-tenant architectures (preferred)
\n%CF; Exposure to project management or ERP systems (nice to have)
\nSoft Skills & Work Approach
\n%CF; Problem Solving: Ability to navigate and understand large, complex codebases
\n%CF; Code Quality: Writing maintainable, well structured code following established
\npatterns
\n%CF; Collaboration: Working with cross-functional teams (frontend, QA, product)
\n%CF; Documentation: Creating clear technical documentation and code comments
\n%CF; Learning Agility: Quickly understanding new domains and technologies
\n%CF; Attention to Detail: Ensuring data integrity and business rule compliance in complex
\nworkflows
\nDesired Technical Skills
\n%CF; Frontend Basics: Understanding of React and REST API consumption patterns
\n%CF; Integration Experience: Webhooks, third-party API integration (QuickBooks, Zapier,
\netc.)
\n%CF; Background Processing: Quartz scheduler or similar job scheduling frameworks
\n%CF; Reporting Engines: Experience with data visualization and reporting libraries
\n%CF; AI/ML Integration: LangChain4j, Spring AI, or similar AI frameworks
\nWhy This Role is Interesting
\n%CF; Complex Domain: Work on sophisticated business logic
\n%CF; Architecture: Learn advanced patterns in multi-tenancy, event-driven design, and
\nextensible systems
\n%CF; Modern Tech: Actively integrating AI/ML capabilities into production
\n%CF; Scale: Navigate and contribute to a large, mature codebase with established
\npatterns
\n%CF; Impact: Your work directly affects project management workflows for enterprise
\nclients\
\n%CF; Growth: Exposure to diverse technical challenges from scheduling algorithms to AI
\nintegration