We are partnering with a leading AI large language model company to hire an AI Solutions Architect to drive the commercial deployment of LLM, Agent and GenAI solutions for enterprise clients.
This is a hands-on, client-facing role for someone who can translate business problems into practical AI solutions, build prototypes, lead POCs, and work closely with product and engineering teams to bring real-world use cases into production.
Key Responsibilities
- Design enterprise AI solutions by applying LLM, Agent frameworks, RAG, multimodal capabilities and other GenAI technologies to real business scenarios.
- Translate ambiguous client requirements into clear solution architecture, technical roadmap, implementation plan and commercial value proposition.
- Lead the full project lifecycle from requirement discovery, solution design and POC to production deployment and post-launch optimization.
- Build core demos and prototypes, including prompt optimization, API integration, Agent workflows, RAG pipelines and basic technical tuning.
- Identify architecture, performance, data and integration challenges during delivery and work with engineering teams to resolve them.
- Evaluate the commercial feasibility, ROI, cost, delivery timeline and scalability of proposed AI solutions.
- Collect client feedback and market insights to support the iteration of the company’s AI platform, LLM products and Agent capabilities.
Requirements
- Bachelor’s degree or above in Computer Science, Artificial Intelligence, Mathematics, Software Engineering or a related discipline.
- At least 1 year of hands-on AI project experience, with involvement in 2 or more LLM-related commercial projects.
- Practical experience with one or more of the following: RAG, enterprise knowledge base, Agent workflow, AI Copilot, multimodal application, intelligent customer service, AI workflow automation or LLM API integration.
- Strong understanding of the GenAI ecosystem, including prompt engineering, LLM APIs, Agent frameworks, RAG architecture, vector databases and system integration.
- Basic coding capability, with the ability to build demos or prototypes using Python, JavaScript, TypeScript or similar languages.
- Strong client-facing communication skills, with the ability to explain technical solutions to both business and technical stakeholders.
- Strong business sense, with the ability to assess solution cost, implementation complexity, delivery timeline and business value.
- Result-oriented, hands-on, and comfortable working in a fast-paced environment.
Preferred Background
- Experience in LLM companies, AI Agent startups, AI-native SaaS companies, cloud AI solution teams, enterprise software companies, consulting firms or system integrators.
- Experience delivering enterprise AI solutions from POC to production.
- Mandarin-speaking candidates are highly preferred.
