Own end-to-end system delivery from architecture to production deployment and operation
Define and evolve core platform architecture for scalability and performance in AI systems
Refactor and reshape critical parts of the stack to meet production-grade standards
Set and enforce engineering standards, leading code reviews and technical excellence
Lead AI inference optimization and latency reduction for real-time AI services

🎯 Requirements

7+ years software engineering with full lifecycle ownership
Strong Python backend development (Flask, FastAPI, or Litestar)
Experience with AWS, GCP, or Azure, Docker, and production deployment
Distributed systems, client-server, real-time protocols (WebSockets/SSE)
Databases and data modeling (PostgreSQL, MySQL, MongoDB, Redis)
Frontend exposure (React, Svelte, or WebAssembly)

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