AI Field Engineer(FDE)

At Singdata, we are building an industry-leading AI-Native data platform and application ecosystem . As a member of Singdata's Singapore AI Innovation Center , you will be at the forefront of Data + AI technologies—combining our powerful data platform capabilities with cutting-edge AI technologies to create enterprise-grade intelligent applications with transformative impact.

Responsibilities

1.Scenario-Driven Application Development

Deeply understand enterprise business scenarios, identify core pain points, and translate them into technical solutions. You will lead the design and development of scenario-specific AI applications, such as intelligent risk control systems, data insight assistants, and more.

2.Understanding Core Architectures of AI Applications

Develop a solid understanding of the following AI application architectural components:

Conversational & Task Frameworks: Build LLM-based conversational engines and agent frameworks capable of autonomously executing complex data tasks.

RAG Engine Optimization: Design and implement efficient, accurate Retrieval-Augmented Generation (RAG) systems with deep integration of structured and unstructured data.

Data-Driven Insight Tools: Develop intelligent analysis tools that automatically detect data patterns, anomalies, and trends.

3.Engineering Excellence & Productization

Drive the process from technology selection and PoC development to full productization. Work closely with product, algorithm, and platform teams to transform technical vision into reliable, user-delighting products.

Requirements (Who You Are)

Strong Computer Science Fundamentals: Solid understanding of data structures, algorithms, operating systems, and networks. Proficient in at least one mainstream programming language (Python/Java/C++/Go).

Experience in Combining Data & AI: Knowledge of machine learning or LLM fundamentals, plus hands-on experience integrating them with modern data tech stacks (e.g., Spark, Flink, Trino, Doris).

Understanding of the AI Application Tech Stack: Familiarity with at least two of the following, with hands-on implementation experience:

LLM application development, including prompt engineering and fine-tuning

Search systems (ElasticSearch, Vector DBs) and RAG architectures

Agent frameworks (LangChain, LlamaIndex) or custom task-planning engines

Product & User-Centric Mindset: Passionate about creating user value. Able to zoom out from technical implementation and shape product experience from the user's perspective. Measure technical success by product outcomes.

Learning & Communication Skills: Ability to learn continuously in a fast-evolving field. Excellent communication skills to articulate complex technical concepts and collaborate across teams.

Nice-to-Have

Proficiency in both Chinese and English

AI application development experience in industries such as finance, insurance, or retail

Experience with MLOps or DataOps, including model deployment, monitoring, and iteration

Contributions to open-source communities or active technical blogging