AESC

About the Project

We are developing SAM (Smart Assistant for Maintenance), an AI-powered assistant designed to help maintenance teams quickly access Standard Operating Procedures 

(SOPs) using natural language queries.

SAM will leverage modern AI technologies such as Retrieval-Augmented Generation (RAG), local Large Language Models, and semantic search to transform how technical  documentation is accessed and used in daily operations. 

The role: 

We are looking for an AI Engineer / Developer to design, build, and deploy the SAM solution. You will work on integrating local AI models, building document retrieval pipelines, and creating a user-friendly interface that enables maintenance teams to interact with SOP documentation efficiently. 

Key Responsibilities

• Design and implement an AI assistant using RAG architecture

• Integrate local LLMs (e.g., via Ollama or equivalent solutions)

• Build document ingestion and semantic search pipelines

• Implement a secure internal knowledge database for SOP documents

• Develop a simple question-answer interface for end users

• Ensure answers are traceable to source documents

• Optimize system performance, reliability, and security

Required Skills

• English profesionnal 

•Strong Python development experience

• Experience working with AI/LLM solutions and open models (e.g., models 

released by Meta)

• Knowledge of Retrieval-Augmented Generation, embeddings, and vector 

databases (e.g., Chroma or similar)

• Familiarity with LLM orchestration tools such as LangChain

• Experience processing technical documents (PDFs, manuals, procedures)

• Ability to build lightweight interfaces (e.g. web, mobile or reactive)

• Understanding of secure or on-premise deployments

Nice to Have

• Experience in manufacturing, maintenance, or industrial environments

• Experience deploying AI solutions in secure corporate infrastructure

• Knowledge of knowledge-management or documentation systems

What Success Looks Like

• Maintenance teams can retrieve SOP information through natural language 

queries

• Answers are reliable, grounded in internal documentation, and traceable

• SOP search time is significantly reduced

• The system is scalable to thousands of documents

Why Join This Project?

• Work on a real-world industrial AI application

• Build a system used directly by operational teams

• Help shape how AI improves knowledge access in manufacturin

Grow and develop your skills in a exigent environement

Le poste est uniquement en apprentissage pour 1 an, sur le site industriel.