You have: Advanced Python proficiency, especially in scalable, clean code architecture and microservices (e.g., FastAPI, Flask, asyncio) Solid understanding of API integration patterns and inter-servic communication (e.g. REST, Kafka) Experience with authentication and authorization mechanisms (e.g. OAuth2, JWT, Azure AD) At least two ML/AI solutions delivered to production, ideally involving document understanding, NLP or search/retrieval systems Practical knowledge and hands-on experience with: RAG architectures, LLMs (e.g., OpenAI, Antropic), Vector databases (e.g., FAISS, Azure AI Search), Embeddings (e.g., OpenAI) Strong grasp of NLP techniques: named entity recognition (NER), document classification, chunking, summarization, question answering. Ability to evaluate trade-offs and select appropriate ML/AI techniques for a given problem. Experience with PoC development and iterating quickly based on results. Familiarity with LangChain, LlamaIndex, or similar agentic frameworks. Strong debugging, profiling, and optimization skills for AI applications.

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