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 AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.

• Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.

• Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).

• DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).

• Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.

• Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.

Candidate Profile

Engineer first, consultant second — with a builder’s mindset and a track record of shipping.

• Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.

• The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.

• The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).

• AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).

• Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).

• Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.

• Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with responsible AI/governance frameworks, security reviews, and cost optimization.

• Domain experience in 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.

• Zurich 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: Zurich

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.

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 AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.

• Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.

• Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).

• DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).

• Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.

• Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.

Candidate Profile

Engineer first, consultant second — with a builder’s mindset and a track record of shipping.

• Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.

• The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.

• The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).

• AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).

• Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).

• Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.

• Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with responsible AI/governance frameworks, security reviews, and cost optimization.

• Domain experience in 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.

• Zurich 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: Zurich

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.

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 AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.

• Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.

• Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).

• DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).

• Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.

• Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.

Candidate Profile

Engineer first, consultant second — with a builder’s mindset and a track record of shipping.

• Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.

• The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.

• The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).

• AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).

• Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).

• Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.

• Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with responsible AI/governance frameworks, security reviews, and cost optimization.

• Domain experience in 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.

• Zurich 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: Zurich

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.

Key Responsibilities

1. Infrastructure Management: Provision, maintain, and upgrade AWS and EKS infrastructure using tools like kubectl, Kustomize, and Helm.
2. Automation & IaC: Develop and document reusable Terraform and Terragrunt modules to automate deployments, backups, and routine maintenance.
3. CI/CD & GitOps: Build and refine CI/CD pipelines using GitHub Actions and GitOps workflows, specifically leveraging ArgoCD (including app-of-apps and ApplicationSets).
4. Monitoring & Reliability: Monitor performance and logs via DataDog and AWS CloudWatch, troubleshoot incidents, and take full ownership of the long-term reliability of the systems you build.
5. Data Platform Support: Support data engineers by operating and improving data platforms or data-adjacent infrastructure (e.g., Airflow/MWAA, SQLMesh) in production environments.
6. Streaming Systems: Support and maintain streaming or real-time data systems to ensure consistent data flow and system uptime.
7. Cost Optimization: Analyze cloud spend using AWS Cost Explorer and Infracost to identify waste and implement cost-saving measures.
8. Operational Support: Assist developers with daily operational needs and maintain security/RBAC and resource efficiency within Kubernetes environments.

As a DevOps Engineer, you are responsible for maintaining and optimizing our AWS and Kubernetes infrastructure to ensure high reliability, security, and scalability. You will focus on driving cost efficiency, accelerating deployment cycles for developers, and piloting emerging tools that deliver measurable value to the organization.

Technical Requirements

1. Kubernetes: Production-level experience with EKS, including Helm and Kustomize.
2. Infrastructure as Code: Proficiency in Terraform and Terragrunt.
3. Cloud & Data Systems: Hands-on experience with the AWS Ecosystem (EC2, ECR, RDS, MSK) and experience operating production data platforms or streaming systems.
4. GitOps: Proven experience with ArgoCD and GitHub Actions automation.
5. Tools: Familiarity with DataDog, MongoDB, and AI-assisted tools like Claude CLI or GitHub Copilot.

Attributes: An intrinsic desire to learn and fill in missing skills, with a proactive approach to conducting proof-of-concepts for new DevOps practices.