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negash/README.md

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Hi there

I am a Developer Leader, AI Engineer, and LLM Application Developer with over 12 years of experience architecting, building, and scaling full-stack applications, enterprise platforms, and zero-to-one products across startup, growth-stage, and highly regulated environments.

As a versatile technology leader and hands-on builder, I thrive in complex, fast-moving environments that require strong ownership, rapid execution, and sound technical judgment. I have extensive experience designing distributed systems, defining scalable architectures, optimizing application performance, and leading engineering teams through all stages of the software development lifecycle.

My expertise spans cloud-native platforms, microservices, AI-powered applications, and enterprise systems, with a strong focus on scalability, reliability, observability, security, and operational excellence. I am comfortable navigating ambiguity, balancing technical debt with business priorities, and making architectural decisions that support long-term growth while maintaining delivery velocity.

My current focus is on applied AI, including large language model (LLM) applications, autonomous agent systems, retrieval-augmented generation (RAG) architectures, and AI-powered product development. I specialize in designing secure, high-performance AI systems that can operate at scale, from experimentation and prototyping through production deployment and continuous optimization.

I am passionate about transforming ambitious ideas into resilient, production-ready solutions that deliver measurable business impact while meeting the highest standards for performance, security, and user experience.

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  1. V2_Bank_recommendation V2_Bank_recommendation Public

    RAG Based An AI-powered Banking recommendation system. It combines semantic search with large language models to generate data-grounded financial recommendations.

    Python 1

  2. V2_Flight_Comparison V2_Flight_Comparison Public

    A deterministic, production-ready flight comparison API built with FastAPI , LangChain structured output , OpenAI , and Amadeus Flight Search , with Opik observability for tracing and evaluation .

    Python 1

  3. AI_10_Best_Practices AI_10_Best_Practices Public

    A practical guide to building cost-efficient AI systems. Covers prompt design, caching, batching, and model selection to reduce token usage, lower costs, and improve performance.

  4. mcp-use mcp-use Public

    Forked from mcp-use/mcp-use

    mcp-use is the easiest way to interact with mcp servers with custom agents

    Python

  5. earthdata-mcp earthdata-mcp Public

    Forked from nasa/earthdata-mcp

    Python

  6. SkillSpector SkillSpector Public

    Forked from NVIDIA/SkillSpector

    Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks.

    Python