Python Backend Engineer | Focus on Async Systems & Scalable Architecture
Backend Development
- Core: Python (Asyncio), Pydantic v2, Static Typing (Mypy).
- Frameworks: FastAPI.
- Data Access: SQLAlchemy v2.0 & Advanced Alchemy (Repository & Service patterns).
- Data Layer: PostgreSQL (Query Optimization), PgBouncer, Alembic, Valkey (Redis fork).
Infrastructure & Quality
- Environment: Linux (Debian 12), Angie (Nginx fork).
- DevOps & CI/CD: Docker & Docker Compose, GitHub Actions, Bash, Dependabot.
- Standards & Tooling: Pytest, Ruff, Conventional Commits, ADR.
- IronTrack — Experimental async sandbox for evaluating architectural patterns under hardware constraints.
- Serialization: Analyzed
msgspecvs Pydantic v2 to minimize overhead in latency-sensitive endpoints. - Concurrency: Offloaded Argon2id hashing to managed thread pools with CPU-core limits to maintain event-loop responsiveness.
- Auth: Evaluated and adopted Ed25519 (EdDSA) to reduce cryptographic compute cost on Piledriver-based hardware.
- Storage Optimization: Tuned PostgreSQL planner and PgBouncer configurations for high-latency HDD environments.
- Decision Log: Architectural rationale and hardware-specific optimizations are documented via ADR and benchmarks.
- Serialization: Analyzed
