Technologies: Spring Boot, Spring Cloud, Netflix Eureka, API Gateway, Circuit Breaker

• Designed and implemented a scalable microservices architecture with 12+ independent services
• Implemented service discovery with Eureka and centralized configuration management
• Built resilient communication patterns using Circuit Breaker and Bulkhead patterns
• Achieved 99.9% uptime with fault-tolerant design and graceful degradation
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Technologies: Apache Kafka, Spring Boot, Kafka Streams, PostgreSQL, Redis

• Developed event-driven order processing pipeline handling 10K+ orders/minute
• Implemented exactly-once semantics for critical financial transactions
• Built real-time analytics dashboard using Kafka Streams for order tracking
• Reduced order processing latency by 70% through event sourcing patterns
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Technologies: gRPC, Protocol Buffers, Spring Boot, Circuit Breaker, Redis Cache

• Built high-performance payment processing service with gRPC for inter-service communication
• Implemented bi-directional streaming for real-time payment status updates
• Achieved 40% reduction in network overhead compared to REST APIs
• Integrated with multiple payment providers with fallback mechanisms
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Technologies: RabbitMQ, Spring Boot, MongoDB, WebSockets, Docker

• Created scalable chat application supporting 50K+ concurrent connections
• Implemented message queuing with RabbitMQ for reliable message delivery
• Built real-time notification system with WebSocket support
• Designed horizontal scaling strategy with load balancing across multiple instances
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Technologies: Spring Boot, LangChain, Pinecone Vector DB, OpenAI API, FastAPI

• Developed RAG-based document analysis system for enterprise knowledge management
• Integrated vector embeddings for semantic search across 1M+ documents
• Built REST API layer for ML model integration with Java backend
• Implemented caching strategies reducing API costs by 60%
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Technologies: Spring Boot, TensorFlow Serving, Redis, Kafka, PostgreSQL

• Architected real-time recommendation system processing 100K+ events/hour
• Integrated TensorFlow models via gRPC for low-latency predictions
• Built feature store with Redis for sub-10ms recommendation serving
• Implemented A/B testing framework for model performance evaluation
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Technologies: Kubernetes, Custom Resource Definitions, Docker, Helm, Java

• Developed custom Kubernetes operator automating Java application lifecycle
• Implemented auto-scaling based on JVM metrics and custom business metrics
• Built deployment strategies supporting canary and blue-green deployments
• Reduced deployment time by 80% through automation
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Technologies: AWS, Terraform, Jenkins, Docker, Kubernetes, GitLab CI

• Designed infrastructure-as-code templates for multi-cloud deployments
• Automated CI/CD pipeline with zero-downtime deployments
• Implemented comprehensive monitoring with Prometheus and Grafana
• Built disaster recovery mechanisms with automated failover
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I'm a Java Backend Architect and AI/ML Integration Specialist with expertise in building high-throughput distributed systems and intelligent applications. Leveraging 4+ years of remote engineering experience, I've architected and implemented enterprise-grade solutions across finance, e-commerce, healthcare, and SaaS domains.

• Backend Architecture: Designing resilient, scalable microservices ecosystems with fault tolerance, circuit breakers, and high availability patterns
• Enterprise Java: Implementing complex business logic with advanced Spring ecosystem features and Java concurrency models
• Cloud-Native Development: Architecting containerized applications with service mesh topologies and infrastructure-as-code workflows
• Performance Optimization: Profiling and tuning JVM applications, database query optimization, and application caching strategies
• AI/ML Integration: Building data pipelines and API interfaces between backend systems and machine learning platforms

As a remote Java backend architect for the past 4+ years, I've led distributed engineering teams to deliver mission-critical systems processing millions of transactions daily. My expertise spans from designing system architecture to implementing robust backend services with enterprise-grade security, scalability, and reliability.

Currently open to new opportunities focusing on:

• Java/Spring backend architecture roles
• Microservices optimization and modernization
• AI/ML integration with enterprise backends
• Cloud-native application development
• Technical leadership positions

• Implementing event-driven architectures with Kafka, RabbitMQ and Apache Pulsar for real-time data processing
• Developing reactive microservices with Spring WebFlux and Project Reactor for non-blocking I/O
• Optimizing database query performance through indexing strategies and query execution plans
• Architecting containerized applications with advanced Kubernetes operators and custom resource definitions
• Building and deploying AI-augmented Java services with vector database integrations and semantic search capabilities

• Distributed systems requiring high throughput and low latency design patterns
• Enterprise backend modernization and microservices decomposition projects
• API gateway and service mesh implementations for large-scale systems
• Data-intensive applications with complex ETL pipelines and real-time analytics
• Machine learning model integration with traditional backend architectures

• Implementing distributed tracing and observability in complex microservice landscapes
• Optimizing Java garbage collection and memory management for large-scale applications
• Designing efficient CQRS and event sourcing patterns for enterprise applications
• Building sophisticated CI/CD pipelines with canary deployments and automated rollbacks
• Developing custom Kubernetes operators for Java application lifecycle management

• Reactive programming patterns with Project Reactor and RxJava
• Domain-Driven Design (DDD) implementation in microservices contexts
• Service mesh architectures with Istio and Linkerd for microservice communication
• Database sharding strategies and distributed transaction management
• JVM profiling, bytecode manipulation, and compiler optimizations
• AI/ML model deployment pipelines using vector databases and RAG architectures

• Distributed transaction patterns (Saga, 2PC, TCC)
• Eventual consistency models and CAP theorem trade-offs
• Fault tolerance design with resilience patterns (Circuit Breaker, Bulkhead, Retry)
• API security with OAuth 2.0, OIDC, and JWT token-based authentication flows
• Microservices testing strategies (contract testing, integration testing)
• Performance bottleneck identification and resolution
• Database indexing strategies and query optimization techniques
• AI/ML model integration with Java backends via REST and gRPC interfaces

• Architecture-first approach to solving complex technical challenges
• Remote-first engineering with asynchronous collaboration practices
• Test-driven development and quality-focused delivery
• Knowledge sharing and technical mentorship
• Continuous learning and technology exploration

I've found that the most powerful backend systems combine traditional enterprise architecture patterns with modern reactive approaches. By integrating event sourcing with CQRS and implementing strategic domain modeling, I've reduced system complexity while improving scalability by orders of magnitude.