Applied AI Engineer - RAG & Knowledge Systems (WW-PT)

Role Overview

We are seeking a skilled Applied AI Engineer to join our team on a part-time contract basis, helping to develop an internal RAG-based investor intelligence platform. You will collaborate with a dedicated engineering team in Singapore, enhancing their CRM development capabilities with your expertise in LLM applications, RAG systems, and AI workflows.

Responsibilities

• Design and construct RAG pipelines for effective investor intelligence retrieval.
• Extract structured insights from various unstructured data sources, including meeting notes and CRM records.
• Develop retrieval workflows utilizing embeddings, vector search, and metadata filtering.
• Architect knowledge systems across semantic search and potentially graph-based frameworks.
• Assess the need for knowledge graphs and relationship mapping within the system.
• Enhance retrieval accuracy and ensure reliable source attribution.
• Conduct evaluations to measure retrieval and answer quality, and minimize hallucination risks.
• Collaborate with the CRM engineering team to integrate AI workflows into existing tools.
• Facilitate future capabilities in recommendations and institutional memory.
• Communicate technical decisions clearly in a remote, asynchronous environment.

Required Skills

• Proven experience in building and deploying production LLM-powered applications.
• Expertise in designing and implementing Retrieval-Augmented Generation systems.
• Strong knowledge in knowledge architecture and graph-based systems.
• Proficiency in extracting intelligence from unstructured business data.
• Ability to evaluate AI system quality and reliability.
• Competence in backend and data engineering to integrate AI workflows.
• Sound judgment in assessing LLM reliability and potential risks.

Nice to Have

• Background in financial services, private markets, or fintech.
• Experience with CRM platforms and relationship intelligence tools.
• Familiarity with human-in-the-loop AI workflows and model monitoring.
• Experience working with graph databases such as Neo4j.
• Knowledge of APAC or Singapore-based team dynamics.
• Strong asynchronous communication skills.