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Focusing
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Focusing
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Achievements

Achievement: Pull SharkAchievement: YOLO

Achievements

Achievement: Pull SharkAchievement: YOLO

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Krrithen/README.md

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Krithin Ravindra Narayan

AI Systems Architect & Backend Engineer | Chicago, IL

Engineering high-throughput distributed systems, scalable microservices, and event-driven AI data pipelines. Focused on latency optimization, vector search retrieval, and resilient infrastructure.

⚡ Core Engineering Focus

  • Distributed Systems: Architecting event-driven microservices (Spring Boot, gRPC) and managing high-volume data streams (Apache Kafka).
  • Search & Retrieval: Optimizing full-text search and inverted indexes (Elasticsearch, Apache Solr) to drastically reduce query latency.
  • AI Infrastructure: Building production-ready RAG pipelines, managing vector embeddings (Pinecone), and orchestrating agentic workflows (LangGraph).
  • Low-Level Systems: Implementing concurrent networking protocols (TCP sockets), thread-safe memory management, and custom parsers in Python.
  • Observability: Deploying cloud-native telemetry and automated alerting (Prometheus, Grafana, CloudWatch) for 99.9% uptime.

🛠️ Technical Stack

Languages & Frameworks
Java Python Spring Boot Node.js

Data & Search
PostgreSQL MongoDB Redis Elasticsearch Apache Solr

Infrastructure & DevOps
Apache Kafka Docker Kubernetes Google Cloud Microsoft Azure Grafana


📊 GitHub Analytics

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  1. Build-Your-Own-Redis Build-Your-Own-Redis Public

    Concurrent, in-memory key-value store built from scratch in Python using raw TCP sockets, multithreading, and custom RESP protocol parsing. Benchmarked at 65k+ ops/sec.

    Python

  2. Distributed-ECommerce-Microservices Distributed-ECommerce-Microservices Public

    Event-driven microservices backend demonstrating gRPC, CQRS with Apache Kafka, and polyglot persistence (PostgreSQL, MongoDB, Elasticsearch).

    Java 3

  3. Cloud-Monitoring-Alerting Cloud-Monitoring-Alerting Public

    Cloud-native observability and alerting stack built with Prometheus, Grafana, and AWS CloudWatch. Reduced incident MTTR by 35% and maintained 99.9% infrastructure uptime.