Kerja Sepenuh Masa AI Engineer, Agentic AI for Fraud Detection | Contract, Gaji tinggi SGD 7,000 di NEXBRIDGE RECRUITMENT PTE. LTD. - Maukerja

Job Responsibilities

Design the end-to-end architecture for FAM agentic AI solutions, including agent orchestration, workflow design, state management, tool integration, human approval points and system interactions, using suitable frameworks such as LangGraph or CrewAI (architecture decisions are subject to consultation with the Platform Team)

Develop AI agents that analyse approved information sources to identify, generate and prioritise evidence-linked emerging fraud and abuse risks for officer review

Develop AI agents that assess data feasibility, propose candidate risk indicators and detection features, and support the translation of validated risks into actionable analytics and detection logic

Integrate agent workflows with FAM 2.0 data and analytics components, including Redshift, Glue and PySpark, and build and maintain the data preparation and feature-engineering processes needed for AI and ML workloads

Convert prototypes into modular, tested, maintainable and deployable services, workflows, APIs or agentic applications, with clear interfaces, version control and operational ownership

Build automated workflows for testing, validation and promotion of code, prompts, workflows and AI components across environments, with quality, security and human approval gates where required

Implement evaluation frameworks and governance controls covering output quality, reproducibility, traceability, access control, exception handling, human approval gates and safeguards against untrusted inputs such as prompt injection

Implement observability, dashboards and alerts covering system health, latency, throughput, errors, resource utilisation, data quality, workflow performance and operating costs

Support incident management, troubleshooting and root-cause analysis

Work closely with data scientists, business users and analysts to capture domain expertise, refine agent workflows and ensure solutions address operational fraud detection needs

Produce maintainable code, architecture decision records, evaluation evidence, operational runbooks and technical documentation, and conduct knowledge transfer to support the long-term sustainability of the solution

Job Requirements

Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related technical discipline

3 years of hands-on experience building and deploying ML/AI applications, including at least one LLM-enabled or agentic AI system delivered beyond prototype into operational use

Strong Python software engineering capability, including API development, testing, version control and modular system design

Experience with LLM applications, retrieval, tool use, workflow orchestration or multi-agent frameworks such as LangGraph, CrewAI or equivalent

Experience integrating AI/ML solutions with enterprise data platforms, databases, APIs or cloud services

Ability to design and implement systematic evaluation frameworks for AI systems, including testing, benchmarking, observability and reproducibility

Working knowledge of AI governance, security and Responsible AI practices, including human-in-the-loop controls, access management, auditability and safeguards against misuse

Strong problem-solving and analytical skills, with the ability to translate business requirements into scalable AI-enabled solutions

Strong engineering judgement and structured experimentation, with the ability to distinguish a robust MVP from a demonstration

Able to explain architecture, evaluation evidence, risks and controls to technical, governance and management audiences

Collaborative working style with fraud-domain officers, designing systems that capture their expertise while leaving decisions and accountability with them

Able to integrate quickly into an existing team and work effectively with limited supervision

Comfortable working across research, engineering, integration, documentation and stakeholder engagement

Experience with AWS services such as Bedrock, Redshift, Glue, S3 or Lambda will be an advantage

Experience with PySpark, Databricks or large-scale data processing and feature-engineering pipelines will be an advantage

Experience with CI/CD, containerisation, MLOps or model deployment tooling (e.g. Docker, MLflow, GitHub Actions, Jenkins) will be an advantage

Experience implementing monitoring, observability and operational support processes for ML/AI applications will be an advantage

Experience delivering fraud detection, risk, compliance, investigation or decision-support solutions will be an advantage

Experience with knowledge retrieval, RAG, graph-based workflows, prompt management, model evaluation tooling or AI observability platforms will be an advantage

Familiarity with Singapore Government or public-sector technology environments, including data governance, security and compliance requirements, will be an advantage

Experience working with cross-functional teams of data scientists, engineers, analysts and business stakeholders will be an advantage

Interested candidates are invited to apply via the “Apply Now” button.

We regret that only shortlisted candidates will be notified.

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Nexbridge Recruitment Pte Ltd

EA License No: 26C3616

EA Personnel: Ching Ning Xin

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