Generative AI Engineer (Energy & Utilities Domain)

bit s.p.a. • Italy

Remote

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AI Summary

Develop advanced Generative AI solutions using Large Language Models (LLM) to analyze and process technical and business documentation in the Energy sector. Design RAG-based systems for document querying, information extraction, and contextual response generation. Integrate AI models into scalable pipelines with a focus on Python and AWS services.

Key Highlights

Design and implement Generative AI solutions for document analysis and retrieval in the Energy domain

Leverage LLM, prompting techniques, and RAG architectures for contextual information extraction

Develop scalable AI pipelines with Python and AWS services (Bedrock, storage, search, and indexing)

Key Responsibilities

Develop AI-driven solutions for extracting, interpreting, and contextualizing information from technical and business documents

Design and implement Large Language Model (LLM) pipelines with Retrieval-Augmented Generation (RAG) techniques

Integrate LLM-based systems into scalable applications and workflows using Python and AWS services

Optimize document parsing, chunking, embedding, and vector search for efficient information retrieval

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Technical Skills Required

Large Language Models (LLM) Python Amazon Web Services (AWS)

Benefits & Perks

Academy gratuita per profili junior

Formazione continua con certificazioni professionali (Oracle, AWS, Microsoft Azure, PMP, ecc.)

Possibilità di lavorare in Smart Working

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Nice to Have

Amazon Bedrock

AWS storage, search, and indexing services

Domain knowledge of Energy & Utilities

Job Description

Siamo alla ricerca di un/una da inserire in un progetto in ambito Energy, focalizzato sullo sviluppo di una soluzione di Intelligenza Artificiale Generativa per l'analisi e l'elaborazione di documentazione tecnica e di business.La risorsa si occuperà dello sviluppo di soluzioni basate su Large Language Models (LLM), finalizzate a estrarre, interpretare e mettere in relazione le informazioni contenute nei documenti, consentendo agli utenti di interrogare la base documentale e ottenere risposte e contenuti contestualizzati.

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