Building production backends + AI features - async APIs, background workers, RAG
📫 Contact: aaryansk73@gmail.com
- 🐍 Python-focused backend engineer working with FastAPI, SQLAlchemy 2.0, Alembic, PostgreSQL, Redis
- 🤖 AI engineer: RAG (LlamaIndex), LLMs, HuggingFace embeddings, incident analysis / root-cause prompts
- ⚙️ Ship with Docker, GitHub Actions CI, Pytest, Ruff
- 📦 Background jobs & realtime: ARQ, Redis Pub/Sub, WebSockets
- 🌱 Previously Java/Spring + React — now focused on Python/FastAPI + AI
1. PulseTrack AI — Uptime monitoring SaaS + AI incident analyst
FastAPI + React SaaS that checks sites/APIs every minute, opens incidents, alerts via Telegram, public status page, Gemini root-cause analysis.
- Backend:
Python 3.12, FastAPI async, SQLAlchemy 2.0, Alembic, PostgreSQL 16, Redis 7, ARQ workers, JWT + API keys, HMAC webhooks - AI:
Gemini 3.5-flash-lite, cached summaries (Redis 24h), 10/min rate-limit, graceful fallback - Quality:
112 Pytest tests, 88% coverage, Ruff clean, GitHub Actions CI (fresh Postgres+Redis), Docker prod images
2. QnA Application — RAG Q&A
RAG app with LlamaIndex + Google Gemini +
BAAI/bge-small-en-v1.5embeddings from HuggingFace.
3. MedicationRecommendationModel — ML recommender
Jupyter + Python recommendation model. Good showcase for data/ML fundamentals.
4. SuperstoreDataVisualization — Python data viz
Python data analysis / visualization.
- 🔭 Maintaining PulseTrack AI
- 📚 Deepening FastAPI async patterns, ARQ, evals for RAG
- 🤝 Open to Python/FastAPI/AI freelance & roles —
aaryansk73@gmail.com