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
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
- ▹Developed AI agent-powered on-call bot — automated codebase analysis for incident diagnosis via Slack, improving team on-call efficiency by 20%
▸AITRICS-VC— Real-time vital sign monitoring and AI prediction system- Python
- FastAPI
- GraphQL
- Docker
- RabbitMQ
- Datadog
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%
▸VODA— Large-scale news and content search service▸VORY-Q— AI-powered data analysis and visualization platform▸AI Canvas— Real-time collaborative AI data labeling platform▸AIVORY— AI-powered web search engine- Python
- Django
- FastAPI
- AWS
- Docker
- Kubernetes
- Redis
- Elasticsearch
Side Projects
recsys-pipeline
Production-grade recommendation pipeline for 50M DAU commerce — 4-Plane architecture with 3-Tier serving, runs locally with docker-compose, scales to 500K RPS on Kubernetes
- ▹3-stage serving: Two-Tower candidate generation → session-aware re-ranking → DCN-V2 GPU scoring
- ▹4-Plane architecture (Data/Stream/Batch/Control) with Envoy, Flink, PySpark, and Airflow
- ▹Cloud-agnostic: single docker-compose up for local development, Kubernetes manifests for production
- Go
- Envoy
- Apache Flink
- Redpanda
- DragonflyDB
- Milvus
- PySpark
- Docker
binance-futures-bot
Automated Binance futures trading bot — technical indicator algorithms with multi-agent trading firm patterns, no AI/LLM required
- ▹8-indicator weighted voting (RSI, MACD, BB, EMA, ATR, ADX, Stochastic) with per-profile signal quality filters
- ▹10-gate risk management: margin exposure limits, daily loss caps, drawdown blocking
- ▹Adversarial signal validation, BM25 situation memory, and post-trade reflection system
- ▹4 trading profiles (Conservative/Neutral/Aggressive/Scalp) with dynamic leverage adjustment
- Python
- ccxt
- pandas-ta
- APScheduler
- Docker
auto-card-news
Automated RSS-to-Threads card news pipeline — fetches news, generates 6-card carousel PNGs, and publishes via Graph API
- ▹End-to-end pipeline: RSS fetch → Playwright scraping → AI summarization → HTML/CSS card rendering → Threads publish
- ▹Immutable frozen dataclass models, URL dedup + publish history for duplicate prevention
- ▹Cloudinary image hosting with automatic cleanup, APScheduler-based periodic execution
- Python
- Playwright
- Jinja2
- Cloudinary
- Threads API
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