All active GitHub Actions roles based in Switzerland.
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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.
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.
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
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.
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.
Ready to apply?
Apply to ArtefactShare this job
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.
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.
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
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.
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.
Ready to apply?
Apply to LinkedIn Job WrappingShare this job
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.
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.
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
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.
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.
Ready to apply?
Apply to Welcome to the Jungle21Shares makes investing in digital assets as easy as buying shares using your conventional broker or bank. Investors can purchase our crypto ETPs easily, safely and securely in a regulated framework on the SIX Swiss Exchange in USD, Euros and GBP, on BX Swiss in CHF, on Boerse Stuttgart in Euros, on DB Xetra as well as Wiener Boerse ( Vienna Exchange) in Euros. We offer the most expansive suite of crypto ETPs available on regulated European exchanges.
Founded in 2018, 21Shares is led by a team of talented entrepreneurs and experienced professionals from the asset management and banking industry. Headquartered in Zurich, the company has launched several exchange-traded products such as NEAR and ONDO in the last twelve months.
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.
Attributes: An intrinsic desire to learn and fill in missing skills, with a proactive approach to conducting proof-of-concepts for new DevOps practices.
Ready to apply?
Apply to 21Shares
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