Key Responsibilities

Design and develop end-to-end agentic AI solutions using frameworks such as LangGraph, CrewAI or equivalent.
Build AI agents to identify emerging fraud risks, assess data feasibility and recommend risk indicators and detection features.
Integrate AI workflows with enterprise data platforms, including AWS Redshift, Glue and PySpark.
Develop and deploy scalable, modular AI applications, APIs and workflows beyond the prototype stage.
Implement CI/CD pipelines, automated testing and deployment processes for AI components.
Establish AI evaluation frameworks and safeguards covering output quality, security, traceability, prompt injection and human approval.
Build monitoring dashboards and alerts to track system performance, reliability, errors and operating costs.
Collaborate with data scientists, analysts, engineers and business stakeholders to translate fraud detection requirements into AI solutions.
Maintain technical documentation, operational guides and architecture records, and support knowledge transfer.

Requirements & Qualifications

Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related field.
3–5 years of hands-on experience developing and deploying AI/ML applications, including at least one LLM-enabled system delivered into operational use.
Strong Python programming skills, including API development, software testing, version control and modular system design.
Experience with LLM applications, tool integration, workflow orchestration or agentic AI frameworks such as LangGraph, CrewAI or equivalent.
Experience integrating AI solutions with databases, APIs, enterprise data platforms or cloud services.
Knowledge of AI evaluation, testing, monitoring, security and Responsible AI practices.
Strong analytical, problem-solving and communication skills.

Preferred Skills

Experience with AWS services such as Bedrock, Redshift, Glue, S3 or Lambda.
Familiarity with PySpark, Databricks, CI/CD, Docker, MLflow or MLOps.
Experience with RAG, knowledge retrieval, graph-based workflows or AI observability tools.
Experience with fraud detection, risk analytics, compliance or investigation systems.
Familiarity with Singapore Government technology environments, data governance and security requirements.
Ability to work collaboratively with technical teams and business stakeholders.

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

We regret that only shortlisted candidates will be notified.

Key Responsibilities

Design and develop end-to-end agentic AI solutions using frameworks such as LangGraph, CrewAI or equivalent.
Build AI agents to identify emerging fraud risks, assess data feasibility and recommend risk indicators and detection features.
Integrate AI workflows with enterprise data platforms, including AWS Redshift, Glue and PySpark.
Develop and deploy scalable, modular AI applications, APIs and workflows beyond the prototype stage.
Implement CI/CD pipelines, automated testing and deployment processes for AI components.
Establish AI evaluation frameworks and safeguards covering output quality, security, traceability, prompt injection and human approval.
Build monitoring dashboards and alerts to track system performance, reliability, errors and operating costs.
Collaborate with data scientists, analysts, engineers and business stakeholders to translate fraud detection requirements into AI solutions.
Maintain technical documentation, operational guides and architecture records, and support knowledge transfer.

Requirements & Qualifications

Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related field.
3–5 years of hands-on experience developing and deploying AI/ML applications, including at least one LLM-enabled system delivered into operational use.
Strong Python programming skills, including API development, software testing, version control and modular system design.
Experience with LLM applications, tool integration, workflow orchestration or agentic AI frameworks such as LangGraph, CrewAI or equivalent.
Experience integrating AI solutions with databases, APIs, enterprise data platforms or cloud services.
Knowledge of AI evaluation, testing, monitoring, security and Responsible AI practices.
Strong analytical, problem-solving and communication skills.

Preferred Skills

Experience with AWS services such as Bedrock, Redshift, Glue, S3 or Lambda.
Familiarity with PySpark, Databricks, CI/CD, Docker, MLflow or MLOps.
Experience with RAG, knowledge retrieval, graph-based workflows or AI observability tools.
Experience with fraud detection, risk analytics, compliance or investigation systems.
Familiarity with Singapore Government technology environments, data governance and security requirements.
Ability to work collaboratively with technical teams and business stakeholders.

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

We regret that only shortlisted candidates will be notified.

ML/AI Engineer | Contract | Gov

Skills