I specialize in architecting highly scalable backend systems, designing production-ready multi-agent AI workflows, and building advanced semantic search infrastructure. I bridge the gap between complex AI research and resilient, production-grade software engineering.
- Core Venture: Co-founding and building Charkh, focusing on integrating complex LLM/AI pipelines directly into scalable production ecosystems.
- Semantic Search & RAG: Architecting enterprise hybrid search pipelines (combining Dense & Sparse embeddings via models like BGE-M3) with heavy-duty vector databases.
- Agentic Workflows: Designing stateful, multi-agent chatbot systems capable of handling dynamic inventory constraints, real-time context management, and external API tool-calling.
- System Performance: Optimizing asynchronous API patterns, data streaming, and efficient indexing strategies for high-throughput applications.
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- Design for Scale: Prioritizing asynchronous event-driven architectures (
asyncio, Celery, Redis) to handle heavy concurrent workloads without blocking threads. - Data-Driven AI: Believing that an AI system is only as good as its data retrieval layer; heavily focused on precision metadata filtering and semantic accuracy.
- Clean, Maintainable Code: Deep adherence to SOLID principles, strict type hinting, automated testing pipelines, and explicit environment isolation.
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I am always open to discussing complex system design, semantic search patterns, or AI integration strategies.
- Project Hub: charkh.io
- Reach Out: Drop me an issue or connect through my project contact channels if you want to collaborate on cutting-edge AI software engineering!