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Report abuseI build robust backend systems using Java, Spring Boot, microservices, custom online apps, Kafka and AWS — and I’m actively exploring Generative AI integration in modern microservices architectures.
Java Full-Stack Engineer | Spring Boot | Kafka | AWS | Microservices | Distributed Systems | Spring AI | LLMs | RAG | Vector Store
I build production-style systems focused on:
- Event-driven architecture
- Saga pattern (Orchestration & Choreography)
- Kafka reliability (DLQ, Idempotency, Outbox)
- Cloud-native deployments (Docker, Kubernetes, AWS)
Production-style saga implementation with compensation handling and event-driven flow. 👉 https://github.com/rady81/saga-orchestration
Retry, DLQ, Idempotency, Manual Ack, Outbox pattern demo. 👉 https://github.com/rady81/event-processing
Serverless architecture with idempotency and failure recovery. 👉 https://github.com/rady81/aws-lambda-serverless-patterns
GenAI utility service that estimates LLMs token usage. 👉 https://github.com/rady81/llm-context-window
- Microservices with Spring Boot 3
- Kafka (KRaft, partitions, consumer groups, offset control)
- Distributed transaction handling (Saga, Outbox)
- Observability (Actuator, logs, correlation IDs)
- AWS deployments (EC2, Lambda, SQS)
- LLMs, RAG, Vector-search
Most repositories include:
- Docker Compose
- Kafka (KRaft mode)
- Postgres
- LocalStack (for AWS demos)
Clone → docker compose up → run Spring Boot → test via Postman.
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