Posted:1 week ago|
Platform:
On-site
Full Time
• Build intelligent, end-to-end data pipelines that utilize large language models (LLMs) for document generation, summarization, reasoning, and automating tasks.
• Design and develop autonomous workflows where AI agents interact with tools, APIs, memory, and other agents to accomplish complex, multi-step objectives.
• Apply prompt engineering, retrieval-augmented generation (RAG), and planning techniques to enable contextual reasoning and decision-making in LLM-powered systems.
• Analyze legacy systems such as rule-based engines, stored procedures, and monolithic applications, and convert them into modular, AI-native components that work with structured and unstructured data.
• Fine-tune foundation models or adapt them using low-rank adaptation (LoRA), transfer learning, or domain-specific techniques for enhanced task performance.
PreludeSys
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