AI Platform Engineer AI平台工程师

Mercedes-Benz Mobility & Technology Service (Beijing) Co., Ltd.

Mercedes-Benz Mobility & Technology Service (Beijing) Co., Ltd., Beijing (Hybrid)

Job Type Full-time

Experience Senior

Posted 2 weeks 6 days ago

Hybrid Senior Level

Tasks

Objective of job: Contribute to the future of Mercedes-Benz Financial Services China by building a secure, scalable and reliable AI platform that accelerates enterprise AI adoption. As part of the AI Hub team, this role designs, operates and continuously improves platform capabilities, tooling and standards that enable AI, generative AI and data-driven solutions to move from experimentation to production efficiently, safely and cost-effectively.

Design, build and maintain the enterprise AI platform foundation, including an on-premises enterprise model and LLM gateway, orchestration, workflow automation, observability and integration capabilities.
Own the Financial Services China Microsoft Power Platform and SharePoint platform, including day-to-day operation, maintenance and change-request development.
Establish and continuously improve LLMOps practices, monitoring and release processes for AI applications.
Provide reusable platform services and engineering standards to help AI software engineers, data engineers and business teams deliver AI use cases faster with lower operational risk.
Ensure the AI platform is secure, compliant, observable, scalable and maintainable in on-premises or regulated enterprise environments.
Optimize performance and cost through resource planning, utilization, capacity management and platform automation.
Contribute to AI architecture, security, governance and technology forums as a platform subject matter expert.

This role combines AI platform engineering with ownership of selected enterprise productivity platforms, especially Microsoft Power Platform and SharePoint, supporting automation, workflow digitization and AI-enabled business processes.

Qualifications

Education: Bachelor’s degree or equivalent professional experience.

Experience: 5+ years of hands-on experience in software engineering, DevOps/SRE, data platform engineering or AI/ML engineering, including practical experience building, operating or supporting production-grade AI/ML, data or application platforms in enterprise environments.

Strong knowledge of DevOps/SRE practices, automation and production operations.
Hands-on experience with containers and orchestration technologies such as Docker and Kubernetes, and familiarity with Linux-based enterprise infrastructure.
Familiarity with LLMOps concepts, including model deployment, monitoring, observability, evaluation and rollback mechanisms.
Good understanding of LLM application stacks and AI engineering patterns, such as RAG, embeddings, vector databases, workflow orchestration and API-based model serving.
Proficiency in at least one programming or scripting language commonly used for automation and platform engineering, such as Python, Java or Go.
Strong communication and collaboration skills.
Financial services, banking or China-regulated enterprise IT experience is a plus.