Job Description

About the Role
We are looking for a Cloud and AI Solutions Architect to support automotive customers and ecosystem partners operating and expanding in markets outside Mainland China. The role will primarily serve automotive OEMs, Tier 1 suppliers, and companies across the broader automotive value chain.
You will work directly with customers' business and technical teams to understand their objectives and real-world challenges, identify high-value AI and cloud opportunities, and translate business requirements into validated, scalable solutions.

This role requires strong cloud architecture expertise as well as hands-on AI capabilities. You should be able to independently design solutions and rapidly validate their technical feasibility and business value through coding, prototyping, and Proofs of Concept (PoCs).
Your primary focus will be customer discovery, solution design, AI prototyping, PoC validation, and technical decision support. For successfully validated solutions, you will collaborate with product, engineering, partner, and delivery teams to support the transition toward production implementation.

The ideal candidate can move comfortably between customer engagement, business problem-solving, architecture design, and hands-on development. You should be able to turn rapidly evolving AI technologies into practical, trustworthy enterprise solutions with the potential to scale.

Key Responsibilities
- Customer Discovery and Solution Design – Work closely with customers' business and technical teams to understand objectives, workflows, data environments, and key challenges; identify and prioritize AI and cloud use cases based on business value, technical feasibility, data readiness, and scalability; translate complex requirements into clearly defined use cases, solution architectures, and validation plans.
- AI Prototyping and PoC Development – Design and build working AI prototypes and PoCs hands-on using technologies such as LLM APIs, RAG, embeddings, vector databases, tool calling, agentic workflows, and multimodal models; integrate AI capabilities with customer data, enterprise applications, and cloud services; design and execute evaluations covering output quality, accuracy, reliability, latency, cost, and safety.
- Cloud and AI Solution Architecture – Design secure, reliable, scalable, and cost-effective architectures based on the company's products and platform capabilities; incorporate data security, privacy, identity management, observability, model governance, and cost control into solution designs; provide architectural recommendations for productionization and support technical handover.
- Pre-sales Support and Enterprise Customer Engagement – Partner with sales and business development teams throughout opportunity discovery, solution design, and customer validation; lead customer workshops, architecture discussions, solution demonstrations, and technical presentations; act as a trusted technical advisor to both technical and non-technical stakeholders.
- Product and Ecosystem Collaboration – Work closely with internal product and engineering teams to communicate customer needs, product gaps, and market opportunities; turn successful engagements into reusable reference architectures, solution templates, and technical playbooks; collaborate with cloud providers, technology partners, and implementation partners to design integrated solutions.