Data & AI Solution Architect

Company Description

Singdata is specializing in next-generation AI and data solutions for modern enterprises. Powered by proprietary technologies Single-Engine and Generic Incremental Compute, Singdata's lakehouse product streamlines data platform architectures, delivering exceptional performance and return on investment. By leveraging AI for Data and Data for AI, Singdata transforms data engineering and analytics processes. Its cloud-agnostic and AI-native data infrastructure powers cutting-edge data agents to drive innovation and efficiency across industries.

Position Description

1. Provide consulting services to key customers on Singdata Lakehouse and AI solutions, driving their Data + AI transformation journey

2. Conduct AI Agent use case discovery, lead solution design and architecture, and drive end-to-end project implementation

3. Work with local sales team to ensure products meet customers business and technical requirements

4. Build reusable solution assets and reference architectures; deliver training, tech talks, and workshops to customers and partners

5. Drive high customer satisfaction in all engagements

6. Travel within APAC is expected (30%)

Core Requirements

1. Bachelor's degree in Computer Science, Engineering, or related field; 5+ years of related work experience

2. Solid skills with at least one mainstream big data platform: Snowflake / Databricks / ClickHouse / Hadoop / Spark

3. Hands-on coding experience, Al coding experience, especially for mission-critical and low-latency systems

4. Experience in architecting and deploying data engineering infrastructure; good understanding of the Big Data industry

5. Fluent English and Mandarin required (speaking and reading) for collaboration with China-based teams.

6. Strong ownership, self-motivation, and passion for helping customers realize business value

AI/LLM Requirements (Preferred)

7. Understanding of LLM fundamentals: model architectures (GPT, LLaMA, Qwen), fine-tuning (LoRA, PEFT), and prompt engineering

8. Experience with RAG systems, vector databases (Milvus, Pinecone, pgvector), and embedding models

9. Familiarity with AI Agent frameworks: LangChain, LlamaIndex, CrewAI, or similar tools

10. Exposure to enterprise AI platforms (Dify, FastGPT) or cloud AI services (AWS Bedrock, Azure OpenAI, GCP Vertex AI) is a plus