AI Engineer - Site: Rome

Aieng; Roma; Hybrid; EUR 55,000 - 85,000; Full time

Job summary

Aieng in Rome, Italy, is seeking an AI Engineer to develop AI-driven solutions, focusing on local inference systems, agentic workflows, and practical applications of Large Language Models within our .NET backend. You will deploy models, build RAG pipelines with vector databases, fine-tune foundational models for engineering domains, and collaborate with Python services that integrate with our C# platform.

Relevant experience with 2+ years in software engineering and a degree in Computer Science

Qualifications

• 2+ years of proven software engineering experience in Applied AI, LLMs, or inference pipelines.
• Degree in Computer Science, AI, or related field; advanced degrees are a plus.

Responsibilities

• AI Deployment & Inference: Deploy and run open-weight models efficiently within the platform.
• RAG & Agentic Workflows: Develop reasoning agents and retrieval-augmented generation pipelines with vector databases.
• Model Fine-Tuning: Adapt and fine-tune foundational models for engineering domains.
• Cross-Functional Collaboration: Build AI services in Python that integrate with the core C#/.NET platform.

Skills

Python

C#/.NET

NLP

LLMs

RESTful APIs

Education

Bachelor's degree in Computer Science or related field

Tools

vLLM

Ollama

Qdrant

Milvus

Weaviate

Job description

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): Practical knowledge of multi-agent architectures or agentic swarms, with the ability to orchestrate complex, distributed reasoning tasks across multiple specialized agents.
• Machine Learning & Computer Vision (Preferred): Experience with traditional Machine Learning pipelines and Computer Vision techniques is highly preferred to support future multimodal capabilities.
• System Integration: Ability to build and expose robust RESTful APIs for AI features, ensuring predictable data flows.

Soft Skills

• Engineering Mindset: Strong analytical, problem-solving, and communication skills, with a focus on delivering working, reliable features.
• Teamwork: Ability to work collaboratively in a hybrid environment, both in-person and remotely.

Experience & Education

• Experience: 2+ years of proven software engineering experience with a strong, demonstrable focus on building and deploying Applied AI, LLMs, or inference pipelines.
• Education: A degree in Computer Science, AI, or a related field is required; advanced degrees are a plus.