AI Architect

My client is an Italian company operating at the intersection of aerospace, Earth observation, and artificial intelligence. They develop innovative near-space platforms capable of acquiring ultra-high-resolution data from the stratosphere, enabling new perspectives for environmental monitoring, defense, and scientific research.
They are currently building a generative GeoAI platform designed to transform complex spatial and visual data into actionable insights through a conversational interface. This platform is meant to understand images, maps, and environmental phenomena, translating them into clear answers and operational decisions.
To support this vision, my client is looking for a Generative AI Architect who will act as the technical and creative core of the platform, designing its cognitive foundations and shaping how language, vision, and geospatial data interact. This role will also play a key part in defining and driving the company's internal AI adoption strategy, helping to build a truly AI-native organization.
Responsibilities Design and develop advanced generative and multimodal AI architectures (text, vision, geospatial data).
Build and optimize training pipelines for LLMs, vision models, and RAG systems using proprietary datasets derived from near-space missions.
Integrate reasoning, generation, and descriptive analysis capabilities for images and maps, converting geospatial data into natural language insights.
Collaborate with data engineering and intelligence teams to create scalable, high-performance AI infrastructure, including distributed and edge deployments.
Experiment with emerging generative AI architectures and methodologies, contributing to the R&D roadmap.
3+ years of experience designing advanced AI architectures, with a strong focus on generative and/or multimodal models.
Hands‐on experience with fine‐tuning, prompt engineering, RAG, vector databases, and embedding models.
Solid foundations in machine learning, deep learning, and data pipelines (Python, APIs, Docker, cloud environments).
Knowledge of MLOps, distributed systems, and large‐scale AI architectures.
Excellent English proficiency (B2+ or higher).
Academic background in Computer Science, Artificial Intelligence, Data Engineering, or related fields.
Experience in computer vision, multimodal reasoning, or geospatial AI.
Familiarity with GIS tools and formats (GeoTIFF, Shapefiles, QGIS).
Work on cutting‐edge generative AI systems powered by real near‐space data.
Direct collaboration with universities, research institutions, and international industrial partners.
Permanent contract with a salary aligned to experience and seniority.
Mid‐Senior level
Full‐time