Principal Engineer (AI & Cloud Infrastructure)
Skills
About the role
Location: Zurich
Technology
In short
In Technology at On, everything we build fuels our mission to ignite the human spirit through movement. We craft technology that improves with every interaction, enhancing the experience for everyone who moves. Delivering Wow through our platforms, apps, and services is a core value.
Your focus will not be on individual use cases or one-off prototypes. Instead, your focus will be AI Platform Engineering: building the paved roads, shared services, and core capabilities that make every AI initiative at On faster to build, cheaper to run, safer to operate, and easier to scale. You will turn scattered experimentation into durable, production-grade capability. You will be a hands-on Principal Engineer who can move from architecture to implementation, from proof of concept to production platform, and from a single workload to a multi-tenant capability serving the entire organisation.
You will work closely with our AI strategy, data science, machine learning, applied AI, and infrastructure leaders, ensuring that On's AI foundations are technically excellent, deeply integrated with our data and systems landscape, and built to serve athletes and customers for years to come.
What Success Looks Like: You will be successful in this role if you turn On's AI ambition into durable engineering capability. You will build a platform that teams across On trust and choose to build on. AI initiatives that once took months of bespoke infrastructure work will ship in days on paved roads. Cost, quality, security, and governance will be managed by design rather than by exception. And as the AI landscape evolves, On's foundations will evolve with it: stable where it matters, adaptable where it counts. You will be the engineering backbone that turns AI possibility into production reality.
Your Mission
Platform & Infrastructure Delivery
Build On's Core AI Platform
Design and deliver the shared services at the heart of On's AI capability: model gateway and orchestration layers, inference serving, retrieval infrastructure, vector and feature stores, evaluation pipelines, and the developer tooling that ties them together.
Provide Paved Roads for AI Development
Create golden paths, SDKs, templates, and reference architectures that allow product and applied AI teams to ship AI features quickly without reinventing infrastructure, security, or governance for each initiative.
Engineer for Production, Not Just Demos
Ensure that AI workloads at On meet the standards expected of any critical system: reliability, observability, latency, cost efficiency, failover, and graceful degradation. Take capabilities from promising prototype to hardened production service.
Own Model Lifecycle Infrastructure
Build and operate the machinery for the full model lifecycle: versioning, deployment, A/B rollout, monitoring, drift detection, evaluation, and retirement, across both third-party foundation models and internally developed models.
Optimise Cost, Performance, and Scale
Establish the practices and tooling to manage inference cost, token consumption, caching, routing between models, and capacity planning, so that On's AI usage scales sustainably with the business.
Engineering & Technical Leadership
Act as a Hands-on Principal Engineer
Lead by example through deep technical contribution. Be comfortable writing production code, designing distributed systems, reviewing critical architecture, and unblocking teams on the hardest infrastructure problems.
Set the Technical Direction for AI Infrastructure
Define the architecture, standards, and long-term technical roadmap for On's AI platform. Make deliberate build-vs-buy decisions across the rapidly evolving AI tooling landscape, and keep the platform coherent as it grows.
Integrate AI Into On's Systems Landscape
Connect the AI platform deeply with On's data platform, identity and access management, event streams, and application ecosystem, so intelligent capabilities can draw on trusted data and act safely within existing systems.
Set a High Technical Bar
Ensure platform components are designed with sound engineering judgement. Balance velocity with quality, simplicity, security, maintainability, and long-term scalability, and raise the bar for AI engineering practice across the organisation.
Navigate Ambiguity With Pragmatism
Work in a space where the ecosystem changes monthly. Use technical judgement, benchmarking, and first-principles thinking to make durable architectural decisions in a fast-moving landscape.
Enablement, Governance & Adoption
Enable Applied AI Teams
Partner closely with applied AI, product, and functional teams as your customers. Understand their needs, remove friction, and shape the platform roadmap around what accelerates them most.
Build Governance Into the Platform
Embed security, privacy, data protection, access control, auditability, and responsible AI guardrails directly into platform primitives, so doing the right thing is the default, not an afterthought.
Establish Evaluation & Quality Infrastructure
Provide the shared evaluation frameworks, benchmarks, regression suites, and observability that let teams measure model and agent quality objectively, and give leadership confidence in what is deployed.
Partner With the AI Circle and AI Kitchen
Contribute actively to On's AI operating rhythm, including the AI Kitchen and AI Circle. Represent the platform perspective in prioritisation discussions and help turn strategic ambition into robust, scalable execution.
Influence Without Authority
Operate as a senior individual contributor who earns trust through expertise, clarity, delivery, and collaboration. Guide teams through professional influence rather than formal management authority.
Innovation & Continuous Improvement
Scout Emerging AI Infrastructure
Continuously evaluate new serving frameworks, orchestration tools, model providers, agent runtimes, and infrastructure patterns, assessing where they can strengthen On's platform.
Evolve the Platform From First Principles
Avoid accumulating tooling for its own sake. Continuously simplify, consolidate, and redesign the platform as the ecosystem matures, retiring what no longer earns its place.
Industrialise What Works
Identify when a capability proven by applied teams should be absorbed into the platform as a shared service, and lead that transition from bespoke solution to reusable foundation.
Promote Responsible AI Use
Ensure platform capabilities are developed and operated with appropriate consideration for security, privacy, data protection, governance, cost, and brand trust.
Mentor and Inspire
Support engineers across On in building strong AI infrastructure skills. Share practical knowledge on distributed systems, MLOps, and LLMOps, and help others develop the judgement to build AI systems well.
Your story
Technical Background
You hold a Bachelor's or Master's degree in Computer Science, Machine Learning, Software Engineering, Data Science, or a related technical field, or equivalent practical experience.
Principal-Level Engineering Experience
You have 10+ years of experience designing and building high-quality, large-scale software systems, with a proven track record as a senior or principal-level engineer operating across complex organisations.
AI/ML Infrastructure Practitioner
You have hands-on experience building the infrastructure behind AI systems: model serving and inference optimisation, retrieval and vector infrastructure, orchestration and agent runtimes, evaluation pipelines, MLOps/LLMOps tooling, and the integration of foundation model APIs into production systems.
Distributed Systems Engineer
You are deeply comfortable with cloud-native architecture, Kubernetes and containerised workloads, event-driven systems, API design, CI/CD, infrastructure as code, and the operational disciplines: observability, SLOs, incident response, that keep critical platforms healthy.
Platform Builder
You have built platforms or internal developer tooling that other engineering teams depend on. You think in terms of paved roads, self-service, multi-tenancy, and developer experience, and you measure your success by the teams you accelerate.
Systems Thinker
You understand how data, platforms, workflows, and business processes connect. You can design shared capabilities that create leverage across an entire ecosystem rather than solving one problem at a time.
Pragmatic Problem Solver
You are excited by complexity, but you do not add unnecessary complexity yourself. You favour simple, elegant, high-leverage architectures that can be understood, adopted, and evolved.
Technology Translator
You can speak equally well with engineers, executives, product managers, and business stakeholders. You make infrastructure trade-offs, costs, and risks understandable, relevant, and actionable.
Impact-Oriented Mindset
You care deeply about outcomes. You are not satisfied with elegant infrastructure that nobody uses. You want to see the platform measurably accelerate how On builds, ships, and operates AI.
Exceptional Communicator
Fluent in English, you can articulate complex technical ideas clearly and persuasively, whether in an architecture review, executive conversation, design document, or cross-functional workshop.
About the Team
Joining the Tech Leadership team at On, you will help accelerate our journey towards becoming an AI-native organisation. In this role, you will design, build, and operate the foundational AI platform that powers intelligent capabilities across On, providing the shared infrastructure, tooling, and services that allow teams throughout the company to build with AI safely, reliably, and at scale.
Zürich
Just by the banks of the Limmat you’ll find our largest global hub in Zürich West – On Labs – where you can hike up 12 floors through our custom-built spiral trail.
Förrlibuckstrasse 190,
8005
Switzerland
Location
What we offer
On is a place that is centered around growth and progress. We offer an environment designed to give people the tools to develop holistically – to stay active, to learn, explore and innovate. Our distinctive approach combines a supportive, team-oriented atmosphere, with access to personal self-care for both physical and mental well-being, so each person is led by purpose.
Build the better you
What to expect
We want to set everyone up for success, so here’s the lowdown on how we hire. Our process is a two-way street – bringing you into our culture, while helping us learn how you think.
Our full process can last about eight weeks from application to offer, because we care about getting it right. These steps explain how we usually do things.
Before you get started, feel free to consider if you want to work with us. Strange question? Well, we give people a lot of space to navigate their day-to-day and that style isn't for everyone. We want you to be passionate about what you do and be sure this is the right fit. Because when skills and passion combine – it creates that 'Wow' moment.
Step One
It starts with you...
You'll start by submitting your application to a specific role. We try to keep this step as simple as possible. We do get a lot of applications, but we review them all. If you're a good fit to the role, a recruiter will follow up with you directly. If you didn't receive a reply, or were unsuccessful this time around, we encourage you to look for other possible matches at On.
Step Two
Interview with a recruiter
What ignites your spirit? This is where we’ll start getting to know all about you and what makes you tick – and it’s your first chance to get a feel for our culture. Chatting with a member of our talent team, you’ll learn more about On and how we work. We’ll learn about what motivates you and what you could bring to the team.
Step Three
Interview with a hiring manager
Ready to dig into the details? This second interview will be held with your future manager and will focus on the specifics of the job. Together you’ll delve into your unique skills and experiences and how they could be relevant at On. It's also a time to assess how you might feel working side-by-side. Bring any questions you have about the job, the team or anything else you might like to know – this is an open forum.
Step Four
The Case Study
What's your style? This task will help us understand how you think, face a challenge and give insight into your novel ideas. Designed to give everyone their best shot, your case study is based on something you might typically experience on the job. This is your chance to show us what you’ve got. So express yourself. Be you.
Step Five
The Experience Day
Your first taste of the Oniverse. This is a time to meet some of the people you'll be working closest with. In person or virtually, you'll get a feel for the day-to-day at On and the people who make it happen. You'll chat with a few potential teammates - the conversations will be as equally driven by the role and your experience as by our values. We believe how you do things is just as important as what you do.
Step Six
The Result
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