What are the responsibilities and job description for the Engineer - Fraud Detection position at Angove Partners?
Engineer – Fraud Detection
Role Overview:
Angove Partners is working with a high-growth Fraud Detection and Risk Technology company building real-time decisioning platforms used by banks, payment providers, and fintechs globally.
These platforms sit directly in the flow of money, making instant decisions on whether transactions, accounts, or behaviours are legitimate or fraudulent.
We’re looking to connect with Engineers across backend, data, and machine learning disciplines who are interested in applying their skills to this problem space. If you’re an engineer interested in working on real-time, high-impact systems in fraud and risk, apply or reach out.
Responsibilities:
- Real-time systems that score and prevent fraud in milliseconds
- High-volume data pipelines and streaming architectures
- Machine learning models that adapt to constantly evolving fraud patterns
- Backend systems and APIs powering risk decision engines
- Improving accuracy by reducing false positives vs missed fraud
- Infrastructure that supports continuous model deployment and monitoring
- Languages: Python, Java, Go, Scala
- Streaming & real-time data: Kafka, Spark, Flink
- Cloud: AWS, GCP
- Datastores: PostgreSQL, Redis, Cassandra
- ML: real-time model serving, feature engineering, experimentation
About you:
We’re keen to connect with Engineers with experience in:
- Backend / Platform Engineering
- Data Engineering (streaming, pipelines, large-scale processing)
- Machine Learning / AI Engineering
- MLOps / Infrastructure
- Data Science / Risk Analytics
- Building or working with production systems at scale
- Interest in real-time data, distributed systems, or applied ML
- Ability to operate in fast-paced, high-growth environments
- Background in fintech, payments, fraud, or high-throughput systems is beneficial, but not essential
If you're working in high-scale backend, data or ML environments and want to move into fraud and real-time risk, get in touch for a confidential conversation.