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║ > Senior Backend Engineer @ PayPay Corporation ║
║ > Data Engineering | Rust | Java/Kotlin | ML/LLM Systems ║
║ > 8+ Years | Tokyo, Japan ║
║ > AWS | Kafka | OpenSearch | RAG | LangChain | OpenAI ║
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Senior Backend Engineer with 8+ years of expertise in architecting and shipping high-throughput, cloud-native applications. Hands-on with Rust, Java 17/Kotlin, and Python, designing microservices with Spring Boot 3, Reactor, gRPC, Kafka, and RabbitMQ—all containerized on Kubernetes/EKS and codified via Terraform & Helm. Increasingly focused on ML/LLM systems — building production RAG pipelines, LLM-powered search with OpenAI & LangChain, vector databases, and integrating ML inference (scikit-learn, XGBoost, PyTorch) into real-time backend services.
- Currently Working: Senior Backend Engineer at PayPay Corporation
- Core Expertise: Backend Engineering, Data Engineering, Rust, Java/Kotlin, Cloud-Native Architecture, ML/LLM Systems
- Experience: 8+ Years across Enterprise, Fintech, Data Engineering, Mobility & ML/AI
- Specializations: RESTful APIs, Microservices, Event-Driven Systems, Database Design, LLM Integration, RAG Pipelines, ML Inference
- Tech Stack: Rust, Java 17, Kotlin, Python, Spring Boot, AWS/Azure/GCP, PostgreSQL, Kafka, OpenSearch, LangChain, PyTorch, scikit-learn
- Reach me: raghavendran.chand@gmail.com
- Location: Tokyo, Japan
- Fun fact: Built systems handling 15k+ req/s and optimized cloud costs by ₹1.6 Cr/year!
| 🏗️ Backend Architecture | 📊 Data Engineering | ☁️ Cloud & DevOps | 🦀 Rust & Systems | 🤖 ML & LLM |
|---|---|---|---|---|
| Spring Boot Microservices | ETL/ELT Pipelines | AWS, Azure, GCP | SQL Parsers & Compilers | RAG Pipelines |
| RESTful APIs & gRPC | Kafka Streams, Airflow | Kubernetes, Docker | High-Performance Systems | LangChain & OpenAI API |
| Database Design & Optimization | Real-time Analytics | CI/CD, Infrastructure as Code | Low-Latency Services | Vector Search & Embeddings |
professional_highlights:
current_impact:
- "Building scalable backend systems at PayPay Corporation serving 65M+ users"
- "Contributed to ML-assisted fraud detection pipeline (XGBoost/SageMaker) at PayPay"
- "Architected production RAG pipeline: GPT-4 + OpenSearch k-NN, sub-100ms p99"
- "Semantic caching with Redis cut OpenAI API costs ~40%"
- "Authored Rust SQL parser improving translation throughput at scale"
ml_achievements:
- "End-to-end RAG system: embedding ingestion → hybrid BM25+k-NN → GPT-4 generation"
- "XGBoost + Gradient Boosting ensemble on SageMaker — sub-50ms fraud scoring at TPS"
- "Integrated scikit-learn Isolation Forest into AT&T ALDB — 35% false-positive reduction"
- "Weekly PySpark retraining pipeline on EMR with blue/green model promotion"
- "Multilingual vector search across 5M+ location records in 3 languages"
technical_achievements:
- "Built NLP search service handling 15k req/s on AWS EKS"
- "Reduced P95 latency by 50% (→ 180ms) via microservices architecture"
- "Cut cloud spend by 20% (~₹1.6 Cr/yr) using Graviton optimization"
recent_projects:
- "ML Fraud Detection Pipeline: XGBoost + SageMaker + Kafka feature store"
- "LLM Place Search with RAG: OpenAI + LangChain + OpenSearch (3× accuracy improvement)"
- "BigQuery-to-Snowflake SQL Translator (50% migration effort saved)"Including all public, private, and organization repository contributions
Includes all private, public, and organization repositories — updated every 6 hours
Open for collaborations, consulting, and interesting conversations about: 🔸 Backend Engineering 🔸 Rust & Systems Programming 🔸 Spring Boot & Microservices 🔸 Data Engineering Solutions 🔸 LLM Integration & RAG 🔸 Cloud Architecture Design
⭐ From Raghav with passion for building amazing systems! ⭐