AI Platform Engineer

AI Platform Engineer About the Role Design, build, and operate the reusable services and engineering assets that power the organization's enterprise AI Platform — a shared capability providing AI services, governance-by-design controls, and reference architectures that accelerate AI delivery across the organization. This is a hands-on, pro-code role requiring strong software engineering and Python capability.

What You'll Do

Design, build, and maintain core AI platform components — LLM inference endpoints, embedding services, vector database infrastructure, agent orchestration layers, and model routers.

Build reusable products (agent harness, memory/context, agent loops, tools, SDKs) that reduce duplication and let teams build faster using common capabilities. Ensure platform services are production-ready, secure, scalable, and well-monitored, with sound reliability engineering and operational practices.

Continuously improve the platform — refining services, exploring new engineering approaches, and enhancing reuse and automation. Partner with the Governance function to embed security, safety, and compliance requirements directly into platform design and engineering patterns.

What We're Looking For Degree in Computer Science, Information Systems, Engineering, IT, or related field. Hands-on experience in software engineering, application development, or platform/AI platform delivery. Strong coding ability in Python, with experience building APIs, services, or automation on cloud platforms.

Good understanding of AI platform components (LLMs, agent frameworks, vector/knowledge services, SDKs) and ability to engineer reusable, adoption-ready patterns. Good understanding of cloud platforms, integration patterns, and operational considerations for shared services.

Understanding of governance-by-design and secure delivery practices for AI platforms. Strong collaboration skills to work across platform, governance, and solution teams. Account Manager Jason He Runfeng EA Licen