Design and scale distributed systems processing graph data at scale with sub-second latency.
Tackle real-world performance and reliability issues via profiling and debugging.
Build a microservices-based stack using Go, Kubernetes, Docker, and Redis.
Write secure-by-design code that safely processes untrusted data.
Productionize AI prototypes into robust, scalable services.

🎯 Requirements

6+ years building and scaling backend systems; strong Python and/or Go.
Full-stack apps: design and deliver for high-traffic environments.
GenAI/ML at scale: production experience with large models.
AI agents/workflows: 1+ year with LangChain/LangGraph/Genkit.
ML systems at scale with data pipelines (Pub/Sub, Kafka).
Ownership mindset: comfortable in remote, fast-paced settings.

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