Senior AI Engineer / Technical Consultant

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.

Romandie Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.

Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.

Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.

Location: Lausanne / Geneva (Romandie)

If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.