You are expected to be an "Individual Contributor" who can lead feature development, mentor juniors, and understand system architecture.

Job Description: Mid-Level Java Developer

Key ResponsibilitiesDesign & Development: Build and maintain scalable, high-performance back-end services using Java 17/21 and Spring Boot.

Microservices Orchestration: Manage service-to-service communication using REST, gRPC, and messaging queues like Kafka or RabbitMQ.

Cloud-Native Integration: Containerize applications using Docker and manage deployments on Kubernetes (K8s) or cloud platforms like AWS (EKS), Azure (AKS), or GCP.

Performance Tuning: Profile Java applications to identify memory leaks, optimize garbage collection, and reduce latency.

Testing & Quality: Lead "Test-Driven Development" (TDD) efforts using JUnit 5, Mockito, and Testcontainers.

Database Management: Design schema and optimize queries for both Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, Redis) databases.

AI-Assisted Engineering: Utilize AI tools (like GitHub Copilot or Cline) for faster refactoring, documentation, and code generation while maintaining quality.

1. Language & Core Fundamentals

Modern Java: Proficiency in Java 17/21 is now the baseline. You should be comfortable with newer features like Records, Sealed Classes, Pattern Matching, and specifically Virtual Threads (Project Loom) for high-concurrency applications.

JVM Internals: A deeper understanding of memory management, Garbage Collection (G1, ZGC) tuning, and using profiling tools like JProfiler or VisualVM to find bottlenecks.

2. Frameworks & Microservices

Spring Ecosystem: This remains the industry leader. You need deep expertise in Spring Boot 3.x, Spring Security 6 (OAuth2/JWT), and Spring Data JPA.

Cloud-Native Frameworks: Knowledge of Quarkus or Micronaut is increasingly valued for serverless and container-first applications due to their fast startup times.

Resilience Patterns: Implementing Circuit Breakers (Resilience4j), Service Discovery, and API Gateways.

3. Data Management

Relational Databases: Advanced PostgreSQL or MySQL (indexing strategies, query optimization, and ACID properties).

NoSQL & Caching: Hands-on experience with MongoDB (document store), Redis (caching/distributed locking), and Elasticsearch (search indexing).

Persistence: Mastery of Hibernate/JPA and understanding the "N+1" problem and caching layers.

4. Distributed Systems & Messaging

Event-Driven Tech: Robust experience with Apache Kafka or RabbitMQ. You should understand concepts like partitions, consumer groups, and idempotency.

Streaming: Basic knowledge of Kafka Streams or Flink for real-time data processing.

5. Cloud, DevOps & Observability

Containerization: Docker and Kubernetes (K8s) are non-negotiable. You should be able to write your own Dockerfiles and k8s manifests.

Cloud Providers: Proficiency in AWS (specifically EKS, Lambda, S3, and RDS) or Azure.

Observability Stack: Monitoring with Prometheus and Grafana; logging with the ELK Stack (Elasticsearch, Logstash, Kibana) or Splunk.

6. Testing & Quality

Automation: Moving beyond basic JUnit 5 and Mockito to integration testing with Testcontainers.

Code Quality: Using SonarQube for static analysis and ensuring high code coverage.

7. AI-Assisted Development

Productivity Tools: Effective use of AI coding assistants like GitHub Copilot or Cursor to accelerate boilerplate generation, refactoring, and unit test creation.

AI Integration: Basic familiarity with LangChain4j for integrating Large Language Models (LLMs) into Java enterprise applications.