Java Software Engineer

o Involved in a team who manages core system development.

o Participate in the overall application lifecycle: requirements analysis, design, development, testing, deployment, and maintenance.

o Write and perform unit and integration tests; leverage AI-driven test generation tools.

o Perform code reviews prior to every pull request and/or merge request.

o Define and communicate technical and design requirements; estimate effort in Story Points.

o Troubleshoot and debug applications; participate in on-call/standby rotations for production support.

o Build and maintain AI-powered workflows using LangChain, Semantic Kernel, or similar frameworks o Develop and deploy Retrieval-Augmented Generation (RAG) pipelines for document Q&A and contextual chat o Integrate LLM APIs (e.g., OpenAI, Azure OpenAI) into backend services and user interfaces

Requirement

• Fluent in English, both written and verbal; experienced in at least 3 full- cycle, enterprise-scale or cross-country projects using English as the working language.
• 5 years professional experience in Java development, with Spring Boot as the primary framework.
• In-depth knowledge of microservice architecture and REST API development using Spring Boot.
• Strong understanding of resilience patterns (retries, circuit breakers, fallback methods) and scalable system design.
• Proficient with:

▪ Spring Framework and its modules

▪ ORM/SQL mappers (Hibernate, MyBatis)

▪ Relational and NoSQL databases

▪ Vector databases (Pinecone, pgsql, Azure AI Search)

• Experience with messaging systems (JMS, Kafka, RabbitMQ, Redis Streams).
• Deep expertise in Spring Security, OAuth2, SSO; ability to conduct security audits and remediate OWASP Top Ten vulnerabilities.
• Mastery of Spring Batch: job orchestration, scheduling, monitoring, error handling, transaction management, and external system integration.
• Skilled in analyzing and modernizing legacy codebases.
• Expertise in JVM performance tuning and concurrency troubleshooting.
• Solid grasp of design patterns (GoF, EIP, Java EE, Microservices) and SOLID principles.
• Strong Linux foundations and scripting skills (Bash, Python); exposure to
• Docker and Kubernetes.
• Familiarity with Spring Cloud for distributed systems is a plus.
• Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK, Splunk) and distributed tracing (Jaeger, Zipkin).
• Proficient with development toolchains: Git/SVN, CI/CD (Jenkins, TeamCity, GitLab CI), configuration management (Ansible, Chef, Puppet).
• Practical experience working with AI-MCP or similar AI-agent ecosystems; able to review, validate, and integrate AI-generated code.
• Experience integrating AI services or frameworks (OpenAI API, LangChain, AWS SageMaker) into production workflows and applying MLOps practices.
• Relevant certifications (Oracle Java, AWS/Azure/GCP, CISSP, CSSLP) are a plus.