AI Engineer
Pubblicato il 13-08-2026 - Altro in Torino
Aieng is a high-growth innovative startup focused on delivering next-generation engineering solutions. We bridge the gap between ambitious vision and technical reality by investing heavily in research, development, and top-tier talent. We are building an intelligent automation platform based on modern microservices, where AI is an active participant in engineering and design processes.
Your Role
As an AI Engineer, your mission is to develop and implement AI-driven solutions, focusing on local inference systems, agentic workflows, and the practical application of Large Language Models. You will actively participate in software development to integrate these intelligent features into our platform, ensuring that AI tools interface seamlessly with our core .NET backend architecture.
Key Responsibilities
AI Deployment & Inference: Deploy and run open-weight models efficiently, ensuring they integrate securely and reliably into our core platform.
RAG & Agentic Workflows: Develop reasoning agents and Retrieval-Augmented Generation (RAG) pipelines,
managing document ingestion and interacting with Vector Databases for contextual retrieval.
Model Fine-Tuning: Help adapt and fine-tune existing foundational models to our specific industrial and engineering domains.
Cross-Functional Collaboration: Collaborate with the engineering team to build AI services in Python that integrate cleanly with our core C# platform.
Technical Skills (Hard Skills)
Software Development: Solid proficiency in Python. Practical familiarity with C#/.NET is a strong plus for cross-ecosystem integration.
Applied AI & NLP: Practical experience with Large Language Models, Natural Language Processing (NLP), and moving AI concepts from theory to working applications.
Inference Ecosystems & Vector Storage: Hands-on experience managing modern local inference ecosystems (e.g., vLLM, Ollama) and integrating them with Vector Databases (e.g., Qdrant, Milvus, Weaviate).
Multi-Agent Orchestration (Preferred): Practic