AI Product Lead

DA FINANCIAL SERVICE (S) PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading financial services firm in Singapore is seeking a talented AI Engineer to drive AI initiatives from inception to deployment. The ideal candidate has a Bachelor's degree in Computer Science or AI and significant experience with LLMs and RAG pipelines. Responsibilities include designing multi-agent systems, collaborating with business teams, and optimizing retrieval-augmented generation. This role offers opportunities for innovation in a dynamic startup environment.

Qualifications

• Strong hands-on experience with LLMs and RAG pipelines.
• Experience leading AI products in startup environments.
• Solid understanding of multi-agent system design.

Responsibilities

• Own AI initiatives from problem definition to deployment.
• Collaborate with teams to create AI-driven solutions.
• Design multi-agent systems using frameworks like LangChain.

Skills

AI System Ownership

Prompt Engineering

Multi-Agent Systems

ReAct-style workflows

Education

Bachelor’s degree in Computer Science or AI

Tools

Vector databases (Milvus, FAISS, Chroma)

AI agent platforms (Coze, Dify, FastGPT)

Job description

Key Responsibilities

AI System Ownership & Delivery

• Own or co‑own AI initiatives from problem definition, technical strategy, architecture design, to production deployment.
• Make informed decisions on model selection,AG architecture, agent orchestration, and system trade‑offs under real‑world constraints.
• Design and optimize LLM inference pipelines, embeddings, and system performance for reliability and scalability.

Product‑Oriented AI Engineering

• Collaborate closely with business, product, and leadership teams to translate ambiguous requirements into AI‑driven solutions.
• Design structured, reusable Prompt Engineering and agent workflows to ensure controllability, robustness, and exploitability.
• Evaluate build‑vs‑buy decisions across models, agent platforms, and infrastructure.

Multi‑Agent Systems & Reasoning

• Design and orchestrate multi‑agent systems using frameworks such as LangChain, LangGraph, MCP, or equivalent.
• Implement reasoning paradigms including ReAct, Chain‑of‑Thought (CoT), Tree‑of‑Thought (ToT).
• Assess and integrate agent platforms (e.g., Coze, Dify, FastGPT) when appropriate.

RAG & Knowledge Infrastructure

• Design and iterate on Retrieval‑Augmented Generation (RAG) architectures.
• Build and optimize knowledge systems using vector databases such as Milvus, FAISS, or Chroma.
• Continuously improve retrieval quality, context grounding, and reasoning accuracy.
• Track emerging AI trends in model alignment, agent systems, and multimodal AI.
• Contribute to internal standards, documentation, prototypes, and technical decision frameworks.
• Mentor engineers or collaborate with external partners when needed.

QUALIFICATIONS

Required

• Bachelor’s degree or above in Computer Science, AI, or a related field.
• Previous experience founding, co‑founding, or being an early technical member of an AI startup, or leading AI products in a startup environment.
• Proven delivery of at least one end‑to‑end AI product (LLM / RAG / Agent‑based system) in production.
• Strong hands‑on experience with LLMs, Prompt Engineering, RAG pipelines, and agent frameworks.
• Solid understanding of ReAct‑style agent workflows and multi‑agent system design.
• Experience making technical decisions under uncertainty, cost, and time constraints.

Nice to Have

• Experience with LoRA / QLoRA, model alignment, or inference optimization.
• Exposure to AI product commercialization, user feedback loops, or go‑to‑market iteration.
• Open‑source contributions, technical writing, or public speaking.
• Strong cross‑functional communication and leadership skills.