Asks for

The ad says“Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure.”
The ad says“Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure.”
The ad says“Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).”
The ad says“Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).”
The ad says“Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph).”
The ad says“Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.”
The ad says“Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure.”
The ad says“Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).”
The ad says“Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph).”
The ad says“AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace.”
The ad says“Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).”
The ad says“Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.”
The ad says“Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).”
The ad says“Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph).”
The ad says“Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.”
The ad says“Core Programming: Mastery of Python and SQL; familiarity with other languages (Java, C++, or Node.js) is a plus.”
The ad says“AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace.”
The ad says“Core Programming: Mastery of Python and SQL; familiarity with other languages (Java, C++, or Node.js) is a plus.”
The ad says“AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace.”
The ad says“Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.”

Who is Artefact?

Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.

With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.

What you will be doing?

We are looking for a Senior AI Engineer / Technical Consultant to bridge the gap between high-level strategy and technical execution. You will act as a "builder first, consultant second," designing and deploying AI/ML solutions that solve complex business problems for global clients. This role involves end-to-end technical leadership, from initial rapid prototyping (PoCs) to scaling production-ready systems.

Key Responsibilities

Solution Engineering: Design, implement, and deploy pragmatic AI solutions (ML, LLMs, Generative AI) tailored to specific client business needs.
Technical Consulting: Act as a technical advisor to client stakeholders, translating business requirements into scalable technical architectures and guiding them on AI best practices.
Prototyping & Production: Build and test Proof of Concepts (PoCs) and transition them into production-ready environments, ensuring security, performance, and maintainability.
Architecture & Infrastructure: Design robust AI infrastructure using cloud-native services (AWS, Azure, or GCP) and modern data pipelines.
Collaboration: Work within cross-functional teams (Data Scientists, Project Managers, and Strategy Consultants) to ensure the technical feasibility of AI initiatives.
Mentorship: Lead project workstreams and mentor junior engineers on technical best practices, MLOps, and coding standards.

Technical Requirements

Experience: 5+ years in Software Engineering, Data Science, or AI/ML development.
Core Programming: Mastery of Python and SQL; familiarity with other languages (Java, C++, or Node.js) is a plus.
AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace.
Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.
Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure.
Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).
Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph).

Qualifications & Soft Skills

Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related STEM field.
Communication: Fluency in English and the local regional language (German or French). Ability to explain complex technical concepts to non-technical business leaders.
Mindset: A "builder’s mindset" with the agility to work in a fast-paced, client-facing consulting environment.
Consulting Experience: Prior experience in a professional services or consulting firm is highly preferred.

What to Expect

Impactful work on global accounts (e.g., Warner Bros, Orange, L'Oréal).
A collaborative "scale-up" environment with a heavy focus on continuous learning and a dedicated training budget.
Opportunity to lead high-visibility projects within the first year.