Agentic AI Platform Engineer

In short

We are looking for an AI Platform Engineer to join the newly established AI and ML Platform team at On.

As one of the fastest-growing global sports brands, investing in autonomous intelligence is critical to On’s strategy and our Company goals for 2026 and beyond.

While our existing squad has built a strong MLOps foundation, we need to inject additional deep, production-grade agentic expertise in the team. In this role, you will partner with your peers to mature the scalability, observability, and governance of our AI platform—ultimately shaping the blueprint for how a global brand leverages AI at scale.

Your Mission

As an AI Platform Engineer, you will play a key role in shaping the technical direction, delivery standards, and architectural quality for agentic solutions within the AI & ML platform space. Your core goals include:

• Build & Operate Agentic Infrastructure: Architect, scale, and maintain highly reliable, secure, and observable core platform components (e.g., evaluation frameworks, routing, gateways) for both internal and customer-facing autonomous use cases.
• Empower Applied Solutions: Act as a trusted partner to business and product teams, providing the tooling and architectural guidance they need to accelerate their adoption of high-impact agentic workflows.
• Contribute to AI & ML Convergence: Bring a deep curiosity for how LLMOps and traditional MLOps intersect, collaborating with peers to explore and test the strategy for a unified, hybrid AI/ML ecosystem.
• Navigate Ambiguity & Champion Standards: Thrive in a fast-paced environment to turn ambiguous requirements into scalable features. You will establish engineering best practices, evaluate cutting-edge tooling, and foster technical consensus across the org.

Your story

You are an expert engineer who pairs deep infrastructure experience with a proven track record in the emerging AgentOps space. You know what "good" looks like in traditional platform engineering, and you have successfully translated that rigor into scaling Agentic AI safely.

• Core Engineering & Production AI Experience: You have a strong background in backend, platform, or data engineering, with a strong preference for candidates who bring prior experience in MLOps or ML Platform engineering.
• For a Mid-Level role: You have 3+ years of overall software engineering experience, with at least 1 year of demonstrable experience building and maintaining production-grade components for Agentic AI / LLM systems.
• For a Senior-Level role: You have 5+ years of overall software engineering experience, with a proven track record of architecting, building, and leading major components of a production agentic infrastructure, far beyond the prototype phase.
• Deep Agentic & Cloud Stack Expertise: You are fluent in modern agentic frameworks, cognitive architectures, and cloud ecosystems (GCP preferred). You know how to architect and interface with core platform components (vector/graph databases, semantic caches, and LLM orchestration gateways) and integrate external systems and tools via modern standards like the Model Context Protocol (MCP).
• Observability & Evaluations: You have experience implementing robust evaluation and observability frameworks (such as LangSmith, LangFuse, etc.) to monitor agent performance, quality, and cost.
• Governance & Velocity: You have a mature, critical perspective on balancing delivery speed with safety, ensuring reliable and secure agent behavior in production without stifling innovation. Collaborative Mindset: You thrive on ambiguous, zero-to-one infrastructure challenges. You are an exceptional, low-ego communicator (both written and verbal) who excels at building consensus, establishing deep partnerships, and earning trust with both technical peers and non-technical stakeholders.