On Holding

5 days ago

Agentic AI Platform Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Build and operate core agentic infrastructure for internal and customer-facing autonomous use cases, including evaluation frameworks, routing, and gateways. Partner with business and product teams to provide tooling and architectural guidance for agentic workflow adoption. Drive AI/ML convergence by bringing expertise in LLMOps and MLOps, while establishing standards for scalability, observability, governance, and secure production behavior within the AI & ML Platform team.

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Architect, scale, and maintain reliable, secure, and observable agentic platform components for internal and customer-facing autonomous use cases.
•Provide tooling and architectural guidance to business and product teams to accelerate adoption of high-impact agentic workflows.
•Drive AI/ML convergence by exploring how LLMOps and MLOps intersect and testing a unified hybrid ecosystem.
•Translate ambiguous requirements into scalable features, establishing engineering best practices and evaluating cutting-edge tooling.
•Mature the scalability, observability, and governance of the AI platform and shape delivery standards and architectural quality.

Key Requirements

•Strong background in backend, platform, or data engineering, with preference for prior MLOps or ML Platform engineering experience.
•For mid-level: 3+ years overall software engineering experience and at least 1 year building/maintaining production-grade components for Agentic AI/LLM systems.
•For senior-level: 5+ years overall software engineering experience, with a track record of architecting/building/leading major production agentic infrastructure components.
•Fluency in modern agentic frameworks and cloud ecosystems (GCP preferred), including integration with core platform components and external systems via modern standards.
•Experience implementing evaluation and observability frameworks to monitor agent performance, quality, and cost, while balancing velocity with safety and governance.

Experience:AgentOpsMLOpsML PlatformLLM systemsBackend engineeringPlatform engineeringData engineering

Skills:Low-ego communicationCollaborationConsensus buildingGovernance mindsetNavigating ambiguity

Languages:English

Tech Stack:GCPVector/graph databasesSemantic cachesLLM orchestration gatewaysModel Context Protocol (MCP)LangSmithLangFuseLLMOpsMLOpsEvaluation frameworksRouting gateways

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

5 days ago

Agentic AI Platform Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Architect, scale, and maintain reliable, secure, and observable agentic platform components for internal and customer-facing autonomous use cases.
•Provide tooling and architectural guidance to business and product teams to accelerate adoption of high-impact agentic workflows.
•Drive AI/ML convergence by exploring how LLMOps and MLOps intersect and testing a unified hybrid ecosystem.
•Translate ambiguous requirements into scalable features, establishing engineering best practices and evaluating cutting-edge tooling.
•Mature the scalability, observability, and governance of the AI platform and shape delivery standards and architectural quality.

Key Requirements

•Strong background in backend, platform, or data engineering, with preference for prior MLOps or ML Platform engineering experience.
•For mid-level: 3+ years overall software engineering experience and at least 1 year building/maintaining production-grade components for Agentic AI/LLM systems.
•For senior-level: 5+ years overall software engineering experience, with a track record of architecting/building/leading major production agentic infrastructure components.
•Fluency in modern agentic frameworks and cloud ecosystems (GCP preferred), including integration with core platform components and external systems via modern standards.
•Experience implementing evaluation and observability frameworks to monitor agent performance, quality, and cost, while balancing velocity with safety and governance.

Experience:AgentOpsMLOpsML PlatformLLM systemsBackend engineeringPlatform engineeringData engineering

Skills:Low-ego communicationCollaborationConsensus buildingGovernance mindsetNavigating ambiguity

Languages:English

Tech Stack:GCPVector/graph databasesSemantic cachesLLM orchestration gatewaysModel Context Protocol (MCP)LangSmithLangFuseLLMOpsMLOpsEvaluation frameworksRouting gateways

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