Position Description

As a Machine Learning Engineer (Agents & Data Intelligence), you will build AI-powered systems that transform how business teams access, analyse, and act on data. You will develop intelligent agents that automate routine analysis, generate insights, and dramatically reduce the time from question to answer—from days to minutes.

You will work across the AI layer of our data stack, building and extending our analysis chatbot (currently SaaS-powered, transitioning to in-house), developing specialised agents for planning, querying, analysis, and monitoring, and enabling the data governance infrastructure needed for company-wide AI-driven analytics. You will collaborate closely with data analysts, data engineers, and business stakeholders.

What You Will Be Doing

AI Agent Development

• Design and implement AI agent workflows powered by LLMs for end-to-end data tasks: natural language queries, automated analysis, reconciliation, and reporting

• Extend and improve our analysis chatbot by developing specialised agents for planning,

  querying, data quality validation, and monitoring

• Extend and optimise our existing RAG framework, including improving document processing,

  chunking strategies, embedding pipelines, and retrieval mechanisms to ground agent responses in our data context

• Develop prompt engineering strategies, few-shot learning, and context optimisation to improve agent

  accuracy and reliability

• Build orchestration frameworks that coordinate multiple specialised agents to solve complex data problems

Data Infrastructure & Governance for AI

• Work with data engineers and managers to build AI-friendly data pipelines that enable rapid AI adoption across the company

• Support implementation of the data access management architecture to enable granular, role-based access control for AI tools

• Build and maintain metric definition frameworks and documentation required for AI agents to accurately interpret business questions

• Develop automated data reconciliation systems including cross-system matching, discrepancy detection, and exception flagging

Automation & Business Impact

• Productionise AI use cases that replace manual processes, such as automated reporting, marketing analytics,

  customer segmentation, or anomaly detection

• Apply traditional ML techniques (anomaly detection, pattern recognition, classification) within agent workflows to

  enhance monitoring and decision-making

• Build quality assurance pipelines that evaluate LLM outputs for accuracy, consistency, and hallucination detection

• Collaborate with data analysts and business teams to identify automation opportunities and eliminate repetitive manual analysis

What You Need to Be Successful

Required

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field

• 3+ years of professional experience in machine learning engineering, data engineering, or

  software engineering with demonstrable ML project delivery

• Strong Python programming skills with hands-on experience using scientific computing libraries and data/visualisation tools

• Working experience with LLM APIs (e.g. OpenAI, Anthropic, or open-source models) and

  practical prompt engineering in production or project settings

• Familiarity with RAG architectures, vector databases, or document retrieval systems

• Solid SQL skills and experience working with cloud data warehouses

• Understanding of software engineering best practices: Git, CI/CD, API design, testing, and containerisation

• Strong analytical ability to translate business problems into technical implementations

• Good communication skills with both technical and non-technical stakeholders

• We welcome all applicants who are eligible to work in Singapore

Nice to Have

• Experience with agent-based AI systems and orchestration frameworks (e.g. LangChain, LangGraph, CrewAI, or similar)

• Familiarity with GCP services (Cloud Run, Cloud Functions, BigQuery)

• Experience with dbt or data transformation frameworks

• Exposure to product analytics tools (e.g. Mixpanel, Amplitude, Firebase)

• Interest in investment, financial services, or cryptocurrency domains

Work Environment

Attractive compensation package with competitive salary and flexible bonus scheme. Individual career path with management and technical growth tracks, enhanced by learning and development programmes. Healthy work environment with company-sponsored medical programme, open communication, and friendly policies supporting work-life balance. We are an equal-opportunity employer and value diversity.