Job Specifications
Required Skills & Experience
Area Expectations
* Core Java / Backend: 7-10+ years of professional experience with Java and related ecosystems; proficiency in Spring Boot, Spring Framework, Spring Data, Spring Security, dependency injection, AOP, configuration, and modularization.
* AI / LLM Integration: Experience integrating or developing AI workflows in Java applications; familiarity with Spring AI or similar frameworks/libraries for embedding models, prompt templates, vector stores, RAG, and LLM orchestration.
* API / Integration: Substantial experience designing and consuming REST APIs, including versioned APIs, request/response patterns, and error handling. Experience with SOAP/WSDL/XML-based services is advantageous.
* Messaging / Eventing: Practical experience with event-driven systems using Kafka, message queues, Pub/Sub, JMS, and understanding of retry mechanisms, partitioning, consumer groups, and schema management.
* UI / Frontend: Experience with frontend frameworks (React, Angular, Vue, etc.), state management, API integration, component design, performance optimization, and responsive design.
* Observability & Monitoring: Background in logging frameworks (e.g., Logback, Slf4j, Log4j2), metrics (Micrometer, Prometheus), tracing (OpenTelemetry, Zipkin, Jaeger), dashboards, alerting, and health endpoints.
* Deployment & DevOps: Knowledge of CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), infrastructure as code, and version control systems.
* Design & Architecture: Competency in clean architecture, domain-driven design, modular systems, design patterns (repository, service, factory, strategy), dependency inversion, and separation of concerns.
* Soft Skills: Ability to participate in design discussions, contribute to technical direction, break down problems, mentor team members, and communicate across cross-functional teams.
Preferred / Nice-to-Have Skills
* Experience with Spring Cloud and microservices ecosystem components (config server, service discovery, circuit breakers, API gateways).
* Familiarity with vector databases and embedding stores (such as Pinecone, Milvus, Redis vector).
* Understanding of domain-driven design, CQRS/event sourcing, and reactive streams (e.g., Reactor, Spring WebFlux).
* Awareness of security frameworks/identity protocols/OAuth/JWT/OpenID Connect in enterprise environments.
* Exposure to serverless or cloud-native AI deployments (AWS Lambda with LLM, Azure AI, Google Vertex AI).
* Experience with on-premises or hybrid deployments, legacy system integration, and modernization efforts.
* Knowledge of multi-agent workflows, AI orchestration, prompt chaining, or agent frameworks.
* Experience implementing feature toggles, A/B testing, or canary deployments.