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Fullstack ai engineer

Pubblicato il 07-09-2026 - Azienda Anonima in Torino

? What we are looking for?
A fast-growing Italian startup is looking for an experienced AI Engineer – Full Stack to join its team and contribute to the design and development of next-generation AI-powered products.

This role is ideal for someone who is comfortable building end-to-end Generative AI systems, from data ingestion and knowledge retrieval to production deployment, while collaborating effectively in a dynamic and fast-paced startup environment.

? Key Responsibilities
- Design, develop, and maintain LLM-based Generative AI pipelines, ensuring high response quality, reliability, and low latency.
- Build and optimize Retrieval-Augmented Generation (RAG) solutions, including chunking strategies, embeddings, vector search, semantic retrieval, and re-ranking.
- Design and implement Graph RAG architectures leveraging knowledge graphs and semantic relationships to improve reasoning and traceability.
- Develop AI Agents and orchestrated workflows using function calling, tool usage, and multi-step reasoning.
- Integrate leading commercial and open-source LLMs (e.g. OpenAI,



Anthropic, Google Gemini, Llama, Mistral), evaluating performance, quality, and cost trade-offs.
- Design and develop scalable REST APIs and backend services exposing AI capabilities to frontend applications and third-party integrations.
- Work with vector databases (Pinecone, Weaviate, Milvus, pgvector) and graph databases (Neo4j) to support knowledge management and intelligent retrieval.
- Collaborate with frontend engineers to deliver conversational interfaces and AI-powered user experiences.
- Optimize AI applications for scalability, reliability, and cost efficiency using cloud-native architectures on AWS or GCP.
- Implement security best practices, authentication mechanisms, and prompt injection mitigation techniques.
- Monitor and evaluate AI systems using model evaluation frameworks, RAG quality metrics, and LLM evaluation methodologies.
- Troubleshoot and improve the entire AI lifecycle

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