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AI Engineer @ .ai
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AI Engineer role is to design and implement intelligent systems using agentic AI capable of autonomous decision-making and task execution by integrating advanced machine learning models with reasoning, planning, and interaction capabilities.
- 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.
- Familiarity with LangChain, LlamaIndex, or similar agentic frameworks.
- Experience with PoC development and iterating quickly based on results.
- Ability to evaluate trade-offs and select appropriate ML/AI techniques for a given problem.
- Strong grasp of NLP techniques: named entity recognition (NER), document classification, chunking, summarization, question answering.
- 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)
- At least two ML/AI solutions delivered to production, ideally involving document understanding, NLP or search/retrieval systems
- Experience with authentication and authorization mechanisms (e.g. OAuth2, JWT, Azure AD)
- Solid understanding of API integration patterns and inter-servic communication (e.g. REST, Kafka)
Skills: Python, LLM, Prompt engineering, Vector databases, RAG architecture, Agentic libraries(Lang chain/Lang graph/Autogen), Computer Vision, Document Processing
Requirements: Python, Azure, Langchain, Kafka Tools: .