Python Developer – AI Systems, LLMs & RAG

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Skills you'll use

What you'll do

• Design, build, and optimize Python-based AI applications leveraging LLMs and RAG for enterprise use cases.
• Develop and deploy custom LLM pipelines, including data preprocessing, model fine-tuning, and inference optimization.
• Implement retrieval-augmented generation workflows integrating embedding generators, retrievers, and contextual generators.
• Engineer robust LangChain, LlamaIndex, or Haystack applications with database and API integrations.
• Build and maintain tool-enabled AI agents capable of reasoning and autonomous task execution (CrewAI, LangGraph, AutoGPT).
• Develop modularized APIs and microservices for internal and client-facing AI features.
• Collaborate closely with ML and data teams on cloud deployment, scalability, and model monitoring (AWS Sagemaker, Azure ML).
• Apply prompt engineering principles to optimize LLM outputs for reliability, contextual accuracy, and performance.
• Maintain and document AI system architectures, data workflows, and integration dependencies. ‍
• Required Skills & Experience

Who can apply

• Develop and deploy custom LLM pipelines, including data preprocessing, model fine-tuning, and inference optimization.
• Implement retrieval-augmented generation workflows integrating embedding generators, retrievers, and contextual generators.
• Engineer robust LangChain, LlamaIndex, or Haystack applications with database and API integrations.
• Build and maintain tool-enabled AI agents capable of reasoning and autonomous task execution (CrewAI, LangGraph, AutoGPT).
• Develop modularized APIs and microservices for internal and client-facing AI features.
• Collaborate closely with ML and data teams on cloud deployment, scalability, and model monitoring (AWS Sagemaker, Azure ML).
• Apply prompt engineering principles to optimize LLM outputs for reliability, contextual accuracy, and performance.
• Maintain and document AI system architectures, data workflows, and integration dependencies. ‍

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