Agentic AI Platform Engineer

ON.com; Greater London; On-site; GBP 120,000 - 170,000; Full time

Job summary

On is seeking an AI Platform Engineer to join the AI & ML Platform team. You will shape the technical direction, deliver scalable and observable agentic infrastructure, and partner with business and product teams to accelerate adoption of agentic workflows.

You should bring a strong backend/platform/data engineering background, 3+ years for mid-level or 5+ years for senior in production agentic AI, and experience with LangSmith/LangFuse and cloud ecosystems (GCP preferred).

Qualifications

• Strong backend/platform experience with ML/AI pipelines.
• Production experience in agentic AI, LLMs, or MLOps.
• Experience with cloud ecosystems and scalable infra.

Responsibilities

• Shape technical direction and delivery standards for agentic solutions.
• Architect, scale, and maintain core platform components and gateways.
• Partner with business and product teams to accelerate adoption of agentic workflows.
• Establish engineering best practices and governance for AI platforms.

Skills

Backend engineering

Platform engineering

MLOps

AgentOps

Cloud ecosystems

Observability

Stakeholder collaboration

Tools

LangSmith

LangFuse

Vector databases

Graph databases

LLM orchestration gateways

Model Context Protocol

Job description

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 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. 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: Strong background in backend, platform, or data engineering; preference for candidates with prior experience in MLOps or ML Platform engineering.
• For a Mid‑Level role: 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: 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: Fluent in modern agentic frameworks, cognitive architectures, and cloud ecosystems (GCP preferred). Skilled at architecting and interfacing with core platform components (vector/graph databases, semantic caches, and LLM orchestration gateways) and integrating external systems via standards like the Model Context Protocol (MCP).
• Observability & Evaluations: Experience implementing robust evaluation and observability frameworks (e.g., LangSmith, LangFuse) to monitor agent performance, quality, and cost.
• Governance & Velocity: Mature perspective on balancing delivery speed with safety, ensuring reliable and secure agent behavior in production without stifling innovation.
• Collaborative Mindset: Thrives on ambiguous, zero‑to‑one infrastructure challenges. Exceptional, low‑ego communicator who excels at building consensus, establishing deep partnerships, and earning trust with both technical and non‑technical stakeholders.

About the Team

The AI & ML Platform team is a newly established pillar within our Data and AI Org, tasked with driving the scale, efficiency, and global velocity of both traditional Machine Learning and next‑generation Agentic AI across On.

We focus on architecting and operating production‑grade infrastructure—from robust LLM gateways and evaluation frameworks to scalable ML pipelines. Beyond building the core engine, we act as trusted partners to teams looking to adopt Agentic AI solutions, providing the guidance, tooling, and best practices they need to implement their use cases successfully.

Our mission is to empower product teams and define a unified AI/ML ecosystem that scales with On’s global momentum.

On is an Equal Opportunity Employer. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination.