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About the role
As an AI Agent Developer (Python) experienced in CrewAI and LangChain, you have the opportunity to join a dynamic AI product engineering team. You will play a crucial role in designing, building, and deploying intelligent agents that address complex challenges at scale by leveraging various cutting-edge technologies. Key Responsibilities: - Develop modular, asynchronous Python applications using clean code principles. - Build and orchestrate intelligent agents using CrewAI, define agents, tasks, memory, and crew dynamics. - Develop custom chains and tools using LangChain. - Implement prompt engineering techniques such as ReAct, Few-Shot, and Chain-of-Thought reasoning. - Integrate with APIs from OpenAI, Anthropic, HuggingFace, or Mistral for advanced LLM capabilities. - Utilize semantic search and vector stores to build RAG pipelines. - Extend tool capabilities, implement memory systems, and leverage DSA and algorithmic skills to structure efficient reasoning and execution logic. - Deploy containerized applications using Docker, Git, and modern Python packaging tools. Qualifications Required: - Proficiency in Python 3.x (Async, OOP, Type Hinting, Modular Design). - Hands-on experience with CrewAI (Agent, Task, Crew, Memory, Orchestration). - Familiarity with LangChain (LLMChain, Tools, AgentExecutor, Memory). - Expertise in Prompt Engineering (Few-Shot, ReAct, Dynamic Templates). - Knowledge of LLMs & APIs (OpenAI, HuggingFace, Anthropic). - Experience with Vector Stores (FAISS, Chroma, Pinecone, Weaviate). - Understanding of Retrieval-Augmented Generation (RAG) Pipelines. - Skills in Memory Systems, Asynchronous Programming, DSA/Algorithms. Joining this team will allow you to work on cutting-edge LLM agent architecture with real-world impact, be part of a fast-paced, experiment-driven AI team, collaborate with passionate developers and AI researchers, and have a significant influence on core product design. As an AI Agent Developer (Python) experienced in CrewAI and LangChain, you have the opportunity to join a dynamic AI product engineering team. You will play a crucial role in designing, building, and deploying intelligent agents that address complex challenges at scale by leveraging various cutting-edge technologies. Key Responsibilities: - Develop modular, asynchronous Python applications using clean code principles. - Build and orchestrate intelligent agents using CrewAI, define agents, tasks, memory, and crew dynamics. - Develop custom chains and tools using LangChain. - Implement prompt engineering techniques such as ReAct, Few-Shot, and Chain-of-Thought reasoning. - Integrate with APIs from OpenAI, Anthropic, HuggingFace, or Mistral for advanced LLM capabilities. - Utilize semantic search and vector stores to build RAG pipelines. - Extend tool capabilities, implement memory systems, and leverage DSA and algorithmic skills to structure efficient reasoning and execution logic. - Deploy containerized applications using Docker, Git, and modern Python packaging tools. Qualifications Required: - Proficiency in Python 3.x (Async, OOP, Type Hinting, Modular Design). - Hands-on experience with CrewAI (Agent, Task, Crew, Memory, Orchestration). - Familiarity with LangChain (LLMChain, Tools, AgentExecutor, Memory). - Expertise in Prompt Engineering (Few-Shot, ReAct, Dynamic Templates). - Knowledge of LLMs & APIs (OpenAI, HuggingFace, Anthropic). - Experience with Vector Stores (FAISS, Chroma, Pinecone, Weaviate). - Understanding of Retrieval-Augmented Generation (RAG) Pipelines. - Skills in Memory Systems, Asynchronous Programming, DSA/Algorithms. Joining this team will allow you to work on cutting-edge LLM agent architecture with real-world impact, be part of a fast-paced, experiment-driven AI team, collaborate with passionate developers and AI researchers, and have a significant influence on core product design.