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Junior AI Engineer

Pubblicato il 28-10-2026 - Aieng in Roma

About Aieng

Tutti i potenziali candidati sono incoraggiati a leggere l'intera descrizione del lavoro prima di candidarsi.

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 a Junior AI Engineer, you will join our engineering team to help build AI-driven features for our platform, working on RAG pipelines, agentic and multi-agent workflows, and local LLM inference. With guidance from senior engineers, you will write Python services that integrate with our core C#/.NET backend.

What You'll Do

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- Build and improve RAG pipelines: document ingestion, embeddings, and retrieval from vector databases.

- Develop reasoning agents and multi-agent workflows, and evaluate their reliability.

- Help deploy and test open-weight models for local inference.

- Build Python AI services and expose them through clean REST APIs that integrate with our C#/.NET platform, in collaboration with the backend team.

Requirements

-

- Good proficiency in Python and basic software engineering practices (Git, testing, REST APIs).

- Hands-on experience (even academic or personal)



building RAG pipelines and agentic workflows with LLMs.

- Practical knowledge of multi-agent architectures (e.g., orchestrating multiple specialized agents).

- Interest in integrating Python AI services with a C#/.NET backend; basic C# knowledge is a strong plus.

- Solid fundamentals in Machine Learning and NLP.

- Degree (or final year) in Computer Science, AI, Mathematics, Engineering, or a related field.

- 0–2 years of experience, including internships or thesis work. Please share a link to your projects

Nice to Have

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- Experience with local inference tools (e.g., Ollama, vLLM, llama.cpp).

- Vector databases (e.g., Qdrant, Milvus, Weaviate).

- Fine-tuning (e.g., LoRA), for example for domain-specific engineering drawing pipelines.

- Computer Vision or OCR experience.

Soft Skills

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- 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.

- Curiosity and willingness to learn fast in a rapidly evolving field.

What We Offer

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- Mentoring from senior engineers and real ownership on industrial AI projects.

- Hands-on growth in RAG, agentic systems, and local LLM inference.

Workplace

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- Hybrid Workplace. xysqume Main Site: Rome.

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