Summary –We are seeking an experienced Finance AI Tech Lead / Solution Architect to lead the architecture, design, and delivery of next-generation AI-powered Finance solutions for enterprise customers. This role serves as the technical leader of the Finance AI team and is responsible for defining end-to-end architecture across data, AI models, applications, integrations, and cloud platforms. The candidate will guide engineering teams, drive architecture decisions, and ensure scalable, secure, and production-ready AI solutions. The ideal candidate combines strong expertise in enterprise architecture, AI technologies, and finance business processes, with the ability to engage customers, influence stakeholders, and lead solution delivery from concept through production deployment.

Key Responsibilities

1. Design scalable, secure and production-ready enterprise AI solutions.
2. Define technical approaches for LLMs, RAG, Agents, APIs and system integrations.
3. Make key technology and architecture decisions.
4. Guide engineers through design, development and production deployment.
5. Ensure solution quality, security, performance, reliability and cost efficiency.
6. Communicate technical decisions and risks to global stakeholders.

Qualification & Required Experience

1. Six (6+) years of hands-on software engineering or solution architecture experience, including proven technical leadership in delivering production-grade LLM / Generative AI / Agent / RAG solutions; POC-only experience is insufficient.
2. Strong understanding of LLM capabilities, limitations and architecture patterns, with practical experience in prompt engineering, RAG pipelines, tool calling, agent orchestration and model evaluation.
3. Proven ability to design scalable, secure and maintainable enterprise AI architectures, covering APIs, data ingestion, vector databases, identity and access management, observability, deployment and integration with existing enterprise systems.
4. Strong hands-on experience with Python and modern backend development, including REST APIs, asynchronous processing, distributed systems and cloud-native deployment.
5. Demonstrated experience leading architecture decisions, conducting technical reviews, resolving complex engineering issues and guiding engineers from solution design through production launch and ongoing optimization.
6. Hands-on experience collaborating with distributed, cross-functional global teams across multiple time zones, including product, engineering, data, security, compliance and business stakeholders.
7. Fluent business English for technical discussions, architecture documentation, stakeholder communication and global meetings (non-negotiable).
8. Working knowledge of enterprise data privacy, security and responsible-AI requirements, including access control, data isolation, sensitive-data handling and auditability.
9. Practical working knowledge of Jira and Confluence for technical planning, documentation, delivery tracking and cross-team collaboration.

Preferred Qualifications (Nice‑to‑Have)

1. Mandarin-speaking capability, to collaborate efficiently with Lenovo China headquarters (strong plus, not mandatory).
2. Hands-on experience with Azure OpenAI / OpenAI API and AI frameworks such as LangChain, LangGraph, LlamaIndex or Semantic Kernel.
3. Experience designing AI solutions for Finance, ERP, Procurement or PTP financial SaaS use cases.
4. Familiarity with Kubernetes, Docker, CI/CD, infrastructure-as-code and production AI observability or evaluation platforms.
5. Experience working within a large multinational enterprise and navigating enterprise architecture, security and governance processes.
6. Relevant cloud or architecture certification, such as Microsoft Azure Solutions Architect, Azure AI Engineer or an equivalent certification.