AI Engineer

About Safran

Safran is an international high-tech group operating in the fields of aeronautics (propulsion, equipment and interiors), space and defense. Its mission: to contribute sustainably to a safer world, where air transport becomes ever more environmentally friendly, comfortable, and accessible. Present on all continents, the Group employs 100,000 people for a turnover of 27.3 billion euros in 2024, and holds, alone or in partnership, world or European leadership positions in its markets. Safran is the 2nd company in the aeronautics and defense sector in TIME magazine's "World's Best Companies 2024" ranking. Because we are convinced that every talent counts, we value and encourage applications from people with disabilities for our job opportunities.

Mission Description

Safran Analytics is Safran Group's IA Factory, specializing in the processing of tabular data, time series, and natural language. Safran Analytics teams work with engineers and product/service managers from Safran Group companies to develop innovative solutions based on Analytics, Machine/Deep Learning, and foundation models. On a daily basis, we dedicate as much time to building (data analysis, data transformation libraries, ML models, SaaS applications, AI Agents) as to deeply understanding field problems in the aeronautics world in its Engineering, Manufacturing, and Services dimensions (product support).

As an AI Engineer, you will join the Technical Directorate of Safran Analytics. You will contribute to the work of product and foundation Squads that operate in agile mode on applications and services based on foundation models and AI agents.

Responsibilities

• Participate in the technical scoping of Safran Analytics AI projects
• Design and develop agents based on LLMs, agent harnesses, and agentic interfaces (mcp, a2a, ag-ui)
• Contribute to the design and implementation of applications that integrate the use of AI agents
• Contribute to Safran Analytics' technical foundations on the subject of agentics: design patterns, AWS architecture, shared services, repo templates
• Contribute to monitoring LLM providers, open source, and commercial solutions for generative AI and agentics
• Optimize costs, latency, and reliability of solutions deployed on cloud (AWS)

Technical Skills

• Advanced proficiency in Python and the GenAI ecosystem
• Agentic architectures: design, implementation, and orchestration of autonomous agents
• Language models: fine-tuning, prompt engineering, evaluation, retrieval
• Cloud & MLOps: AWS (SageMaker, Lambda, etc.), containerization (Docker), CI/CD, monitoring
• Software development best practices: testing (unit, integration), versioning, clean code architecture

Personal Aptitudes

• Curiosity & appetite for discovering business domains: passion for understanding complex fields, industrial processes, business constraints.
• Ability to learn quickly and ask the right questions
• Enjoyment of knowledge sharing: passion for demystifying complexity and making it accessible
• Ability to train and support: pedagogical approach and benevolence towards other teams
• Multidisciplinary mindset: ease in discussing with business experts, domain engineers, and developers
• Technical rigor and creativity to innovate in a rapidly evolving field, while respecting high-tech constraints

Additional Assets Appreciated

• Experience in open source: contribution, maintenance, or leadership of projects
• Proficiency in architecture patterns for distributed and scalable systems
• Experience with LLMs in production (costs, latency, reliability, security)
• Knowledge in knowledge management or automatic process treatment
• Experience or strong interest in industry (aeronautics, defense, automotive, energy, manufacturing, etc.)

Qualifications

We are looking for a curious AI Engineer passionate about industrial challenges. Master's degree (Bac+5) or engineering degree in applied mathematics, computer science, data science, or related disciplines. Minimum of 2 years of concrete experience in Generative AI development (LLMs, agents, RAG, fine-tuning, orchestration, etc.).