Data & AI Solution Architect

About Singdata

Singdata specializes in advanced AI and data solutions tailored for contemporary enterprises. Their innovative lakehouse product utilizes proprietary technologies—"Single-Engine" and "Generic Incremental Compute"—to simplify data platform architectures, enhancing performance and maximizing investment returns. By integrating AI for data processing and data for AI enhancement, Singdata revolutionizes data engineering and analytics. Their cloud-independent, AI-native infrastructure supports state-of-the-art data agents, fostering innovation and operational efficiency across various sectors.

Role Overview

In this role, you will deliver expert consulting on Singdata's Lakehouse and AI solutions to key clients, guiding their Data and AI transformation journeys. Responsibilities include discovering AI Agent use cases, leading solution architecture design, and managing full-cycle project execution. Collaborating closely with the local sales team, you’ll ensure product alignment with customer business and technical needs. Additionally, you will create reusable solution assets and reference architectures and conduct training sessions, technical presentations, and workshops for clients and partners. Maintaining high customer satisfaction throughout engagements is a priority. Travel within the APAC region is expected at approximately 30%.

Essential Qualifications and Skills

• Bachelor's degree in Computer Science, Engineering, or a related discipline along with over five years of pertinent work experience.
• Strong proficiency in at least one major big data platform such as Snowflake, Databricks, ClickHouse, Hadoop, or Spark.
• Practical coding skills and AI programming experience, particularly in mission-critical and low-latency system environments.
• Expertise in designing and implementing data engineering infrastructures with a robust understanding of the Big Data ecosystem.
• Fluency in both English and Mandarin for effective collaboration with teams based in China.
• Demonstrated self-drive, ownership, and enthusiasm for enabling customers to extract business value from technology.

Preferred AI and LLM Competencies

• Comprehensive knowledge of LLM fundamentals, including model architectures such as GPT, LLaMA, and Qwen, as well as fine-tuning techniques like LoRA and PEFT, and prompt engineering.
• Experience working with Retrieval-Augmented Generation (RAG) systems, vector databases including Milvus, Pinecone, and pgvector, and embedding model technologies.
• Familiarity with AI Agent frameworks such as LangChain, LlamaIndex, CrewAI, or comparable tools.
• Exposure to enterprise AI platforms like Dify, FastGPT, or major cloud AI services including AWS Bedrock, Azure OpenAI, and GCP Vertex AI is advantageous.