On Holding

1 day ago

Principal Engineer (AI & Cloud Infrastructure)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 29 minutes agoStatus: Live

Job Summary

Build and operate On’s core AI platform by delivering shared infrastructure and “paved roads” for AI development. Own model lifecycle systems (serving, orchestration, evaluation, monitoring, drift detection, and rollout) and ensure production-grade reliability, observability, cost efficiency, and secure governance. Lead technical direction as a hands-on principal engineer, integrate the platform with data and systems, and enable applied AI teams through evaluation frameworks, tooling, and developer enablement.

Location: Zurich

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and deliver shared AI platform services, including model gateway/orchestration, inference serving, retrieval infrastructure, vector/feature stores, and developer tooling.
•Create “paved roads” (SDKs, templates, and reference architectures) that help product and applied AI teams ship AI features without rebuilding core infrastructure, security, or governance.
•Engineer production-grade AI workloads with reliability, observability, latency, cost efficiency, failover, and graceful degradation from prototype to hardened services.
•Own model lifecycle infrastructure across third-party and internally developed models, including versioning, deployment, monitoring, drift detection, evaluation, and retirement.
•Set technical direction and raise the bar for AI engineering through architecture standards, integration with data/identity/event streams, enablement of applied teams, and mentorship.

Key Requirements

•10+ years designing and building high-quality, large-scale software systems across complex organizations.
•Hands-on experience with AI/ML infrastructure, including model serving and inference optimization, retrieval/vector infrastructure, and MLOps/LLMOps tooling.
•Deep comfort with cloud-native architecture, Kubernetes and containerized workloads, event-driven systems, API design, and CI/CD.
•Experience building platforms or internal developer tooling that other engineering teams depend on, with a focus on multi-tenancy and developer experience.
•Fluency in English and the ability to clearly communicate complex technical trade-offs to engineers and business stakeholders.

Experience:10+ yearsAI/ML infrastructureMLOps/LLMOpsCloud-nativeDistributed systems

Education:

Skills:Technical leadershipSystems thinkingPragmatic problem-solvingCommunication

Languages:English

Tech Stack:Cloud-native architectureKubernetesContainerised workloadsEvent-driven systemsAPI designCI/CDInfrastructure as codeObservabilitySLOsIncident responseMLOpsLLMOpsModel servingRetrieval infrastructureVector storesFeature storesEvaluation pipelinesDrift detectionA/B rollout

Company Brief

On Holding

Designs, manufactures, and sells performance running shoes, apparel, and accessories under the On brand. Combines Swiss engineering and innovation with lifestyle design to serve runners and athletes globally through retail and direct-to-consumer channels.

Industry: Fashion & Apparel

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Zurich, Switzerland

Founded: 2010

Glassdoor: 4.0

Website LinkedIn

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On Holding

1 day ago

Principal Engineer (AI & Cloud Infrastructure)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 29 minutes agoStatus: Live

Job Summary

Location: Zurich

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and deliver shared AI platform services, including model gateway/orchestration, inference serving, retrieval infrastructure, vector/feature stores, and developer tooling.
•Create “paved roads” (SDKs, templates, and reference architectures) that help product and applied AI teams ship AI features without rebuilding core infrastructure, security, or governance.
•Engineer production-grade AI workloads with reliability, observability, latency, cost efficiency, failover, and graceful degradation from prototype to hardened services.
•Own model lifecycle infrastructure across third-party and internally developed models, including versioning, deployment, monitoring, drift detection, evaluation, and retirement.
•Set technical direction and raise the bar for AI engineering through architecture standards, integration with data/identity/event streams, enablement of applied teams, and mentorship.

Key Requirements

•10+ years designing and building high-quality, large-scale software systems across complex organizations.
•Hands-on experience with AI/ML infrastructure, including model serving and inference optimization, retrieval/vector infrastructure, and MLOps/LLMOps tooling.
•Deep comfort with cloud-native architecture, Kubernetes and containerized workloads, event-driven systems, API design, and CI/CD.
•Experience building platforms or internal developer tooling that other engineering teams depend on, with a focus on multi-tenancy and developer experience.
•Fluency in English and the ability to clearly communicate complex technical trade-offs to engineers and business stakeholders.

Experience:10+ yearsAI/ML infrastructureMLOps/LLMOpsCloud-nativeDistributed systems

Education:

Skills:Technical leadershipSystems thinkingPragmatic problem-solvingCommunication

Languages:English

Company Brief

On Holding

Industry: Fashion & Apparel

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Zurich, Switzerland

Founded: 2010

Glassdoor: 4.0

Website LinkedIn