ML/AI Engineer (Fraud Analytics Model) - Government Project
Core
Design and build agentic AI systems to detect misuse of public training subsidies and convert validated risks into actionable detection logic.
Role type
Senior IC ML/AI Engineer (Fraud Analytics)
Builds
Agentic AI solutions, detection logic, and data preparation pipelines for fraud detection
Domain
Public sector / Fraud analytics / AI
Deliverable
production ML models
Required skills
Python software engineering, LLM applications, agentic AI frameworks (LangGraph, CrewAI), workflow orchestration, data integration (Redshift, Glue, PySpark), evaluation frameworks, AI governance
Preferred skills
AWS services (Bedrock, Redshift, Glue), PySpark, Databricks, CI/CD, containerisation, MLOps
Technologies
LangGraph, CrewAI, Redshift, Glue, PySpark, AWS Bedrock, Docker, MLflow
Responsibilities
Design end-to-end architecture for agentic AI solutions, develop AI agents for emerging risk and detection engineering, integrate agent workflows with data platforms, convert prototypes to deployable services, build CI/CD automation, implement evaluation frameworks and guardrails, monitor system health and reliability, collaborate with data scientists and business users
Seniority
Mid-Senior, hands-on IC
