AI Engineer
Pubblicato il 22-08-2026 - TXT GROUP in Cologno Monzese
TXT Group is looking for an AI Engineer – LLM & RAG Systems to join our team dedicated to developing cutting-edge Generative AI solutions.
The successful candidate will be involved in the design, development and evolution of Agentic AI and Retrieval-Augmented Generation (RAG) systems, contributing to the delivery of reliable, scalable and cost-effective Large Language Model (LLM)-based solutions that address real business needs.
Main Responsibilities
Design and implement end-to-end agentic systems, including orchestration, intent classification, request routing, and query rewriting and expansion;
Define and maintain prompt engineering strategies tailored to different use cases;
Select and optimise LLM and embedding models based on quality, latency and cost;
Develop ingestion pipelines for unstructured data, including document parsing, cleaning, normalisation, chunking and metadata extraction;
Implement embedding generation pipelines and manage vector databases;
Design advanced retrieval strategies, including RAG, hybrid search and reranking techniques;
Implement function/tool-calling patterns and integrate external tools (databases, applications, Machine Learning models and web search) using the MCP protocol;
Develop entity and relationship extraction processes to build knowledge graphs that enhance retrieval capabilities;
Define evaluation metrics and frameworks for RAG and LLM systems, measuring retrieval quality, answer correctness and relevance, hallucination detection, and developing regression testing suites for prompts and pipelines;
Design mechanisms to collect and analyse user feedback, supporting offline evaluation and potential model fine-tuning activities.
Required Technical Skills
At least 2 years of experience developing solutions based on Large Language Models;
Strong Python skills and proven experience developing end-to-end LLM-based applications;
Experience with LLM and agent orchestration frameworks (such as LangChain, LlamaIndex or equivalent