# Senior AI Engineer / Technical Consultant at Artefact > Switzerland · Senior · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Aartefact%3A8270870002 (read 2026-11-06). ## Facts (observed) - Company: [Artefact](https://alderhq.app/companies/artefact) - Location text: Lausanne, Vaud, Switzerland; Lausanne - Where it can be done from (inferred): Switzerland (evidence: "Location: Lausanne, Vaud, Switzerland; Lausanne") - Posted: 2025-11-09 (362 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://job-boards.greenhouse.io/artefact/jobs/8270870002 - Skills listed (inferred): TypeScript, Python, FastAPI, Java, Scala, Elasticsearch, AWS, GCP, Azure, Kubernetes, Docker, SQL, PyTorch, TensorFlow, LLMs, Distributed systems ## Pay and sponsorship - Posted pay: not posted ## Description (the employer's text) ### 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. ### Main Responsibilities As a Senior Technical Consultant / Senior AI Engineer, you will lead the design and delivery of impactful AI and data solutions. You’ll combine hands-on engineering with client advisory, guiding multi-disciplinary teams from opportunity framing to production deployment. Own solution architecture & delivery: Define end-to-end architectures (data, ML/LLM, APIs, security), make build/buy decisions, and drive projects from PoC to production with reliability, observability, and cost in mind. Lead complex PoCs & pilots: Scope, prototype, and validate AI/ML use cases (incl. LLMs/GenAI, RAG, fine-tuning, evaluation) and convert successful pilots into scalable products. Advanced programming & modeling: Build, adapt, and evaluate ML/DL/LLM models using Python (PyTorch, TensorFlow, HuggingFace, LangChain/LlamaIndex), including prompt engineering, fine-tuning/LoRA, vector search, and safety/guardrails. Cloud & MLOps/LLMOps: Design and operate solutions on Azure, GCP, or AWS (CI/CD, containers, model serving, feature stores, vector DBs, monitoring, eval pipelines). Client advisory & stakeholder management: Translate business goals into technical roadmaps, present to senior stakeholders, manage risks and trade-offs, and ensure measurable business impact. Quality, security & governance: Enforce best practices on data privacy, model risk management, responsible AI, and documentation. Team leadership & mentoring: Coach engineers/consultants, perform code and design reviews, and help shape delivery standards and reusable accelerators. Pre-sales & thought leadership: Support proposals, estimates, and statements of work; contribute to assets, talks, and publications that advance Artefact’s AI offering. ### Candidate Profile Engineer first, consultant second — with a builder’s mindset and a track record of shipping. Experience: 5–8+ years in data/ML/AI engineering or adjacent roles, including end-to-end delivery of production AI systems (not just prototypes). Programming: Expert Python; solid software engineering (testing, packaging, CI/CD). SQL required; Java/Scala/TypeScript a plus. AI/ML: Hands-on with ML/DL and LLMs (prompting, fine-tuning/LoRA, embeddings/RAG, evaluation & observability, guardrails). Cloud: Deep experience on at least one major cloud (Azure, GCP, or AWS) deploying secure, scalable services. MLOps/LLMOps: Containers (Docker/Kubernetes), Git, pipelines (e.g., GitHub Actions/Cloud-native), model serving (FastAPI/TorchServe/Triton), experiment tracking, model registry, vector DBs (FAISS, Pinecone, pgvector, OpenSearch). Architecture & data: Designing data/ML platforms, APIs, microservices; familiarity with data pipelines and streaming is valued. Consulting skills: Requirements gathering, storytelling, senior stakeholder management, and clear documentation. Languages: Fluency in French and English (written & spoken) is mandatory. Work eligibility: You must be eligible to work in Switzerland. Nice to have Experience with responsible AI/governance frameworks, security reviews, and cost optimization. Domain experience in one or more industries (e.g., retail, pharma, manufacturing, finance). Contributions to open-source, publications, or conference talks. ### Why Join Us Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aartefact%3A8270870002 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.