Kikang Kim

Backend Engineer

I design stable and scalable service architectures.

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About

Backend engineer with 5+ years of experience, specializing in Python. Experienced in large-scale traffic handling on AWS, real-time data pipeline design, and search engine optimization. Achieved 94.8x throughput improvement through Pub/Sub architecture and contributed to growing a service from 300K to 10M+ monthly page views.

Experience

  1. Aug 2024 — Present

    Backend Engineer · AITRICS

    • ▹Migrated REST API to GraphQL, enabling precise data fetching, eliminating over-fetching, and improving client development productivity
    • ▹Redesigned scheduler-based batch processing to RabbitMQ Pub/Sub architecture, achieving 94.8x average throughput improvement with per-patient event processing and real-time alerts
    • ▹Implemented message failover strategies including Retry, DLQ, and Sequence management for reliable message processing
    • ▹Built Datadog-based APM dashboards, error rate tracking, service health monitoring, and on-call alerting
    • Python
    • FastAPI
    • GraphQL
    • Docker
    • RabbitMQ
    • Datadog
  2. Nov 2020 — Aug 2024

    Backend Engineer · Plan.I

    • ▹Owned end-to-end backend design and operations for multiple B2B/B2C services including VODA, VORY-Q, AI Canvas, and AIVORY
    • ▹Built behavioral data collection pipeline using AWS API Gateway + SQS, supporting growth from 300K to 10M+ monthly PV
    • ▹Managed GPU resources on Kubernetes and designed a Redis-backed workload-aware job scheduler
    • ▹Optimized Elasticsearch incremental indexing, reducing data visualization processing time by up to 95%
    • Python
    • Django
    • FastAPI
    • AWS
    • Docker
    • Kubernetes
    • Redis
    • Elasticsearch

Projects

  • 2024

    AITRICS-VC

    Designed backend architecture for real-time vital sign monitoring and AI prediction system

    • ▹Redesigned batch pipeline to event-driven Pub/Sub, achieving 94.8x throughput improvement
    • ▹GraphQL migration eliminating over-fetching and improving API abstraction
    • Python
    • FastAPI
    • GraphQL
    • RabbitMQ
    • Docker
  • 2023.06 — 2024.01

    AI Canvas

    Backend development for real-time collaborative AI data labeling platform

    • ▹GPU resource management via K8s with Grafana monitoring
    • ▹Redis-backed workload-aware scheduler supporting ~100 concurrent users within ~10s
    • Python
    • FastAPI
    • WebSocket
    • Redis
    • Docker
    • AWS
  • 2022.05 — 2022.12

    VORY-Q

    Backend development for AI-powered data analysis and visualization platform

    • ▹LRU caching for concurrent collection/recommendation, API response under ~1s
    • ▹Daily pre-aggregation reducing visualization latency by 90%
    • Python
    • Django
    • Celery
    • PostgreSQL
    • Redis
  • 2021.05 — 2022.04

    VODA

    Designed and operated backend systems for large-scale news and content search service

    • ▹Behavioral data pipeline via API Gateway + SQS, scaling 300K to 10M+ monthly PV
    • ▹MSA architecture, visualization processing time reduced by up to 95%
    • Python
    • Django
    • Elasticsearch
    • AWS
    • Nginx
    • Jenkins
  • 2020.11 — 2023.04

    AIVORY

    Developed indexing and search systems for AI-powered web search engine

    • ▹Optimized incremental indexing—selective data fetching, post-reference memory cleanup
    • ▹Oracle DB indexing support, automated installation scripts
    • Python
    • Elasticsearch
    • Docker
    • AWS
    • Redis

Skills

Languages

  • Python
  • SQL

Frameworks

  • FastAPI
  • Django
  • GraphQL
  • REST

Infrastructure

  • Docker
  • Kubernetes
  • Nginx
  • Jenkins
  • CI/CD

Cloud

  • AWS EC2
  • S3
  • RDS
  • SQS
  • API Gateway
  • OpenSearch
  • Lightsail

Data

  • PostgreSQL
  • Redis
  • Elasticsearch
  • RabbitMQ
  • Celery

Monitoring

  • Datadog
  • Prometheus
  • Grafana

Testing

  • pytest
  • TDD