Teya is looking for a highly technical Senior Fraud & Transaction Monitoring Engineering Manager to lead the analytical backbone of our fraud and AML monitoring capabilities. This role focuses on building, optimising, and scaling the detection systems, rule engines, behavioural signals, and data flows that protect our ecosystem. You will be the technical owner of how monitoring systems work end-to-end.
What You'll Do
- Act as the technical lead for the fraud & AML rules engine, risk scoring logic, and behavioural monitoring pipeline.
- Design and improve the event flows, data schemas, triggers, and scoring components used for detection.
- Work closely with engineering to implement scalable and low-latency monitoring logic in production.
- Lead analysts in designing and refining technical detection rules (syntax, thresholds, conditions, event mapping).
- Translate risk appetite into robust, efficient, and data-backed rules.
- Create testing frameworks, simulation tools, and regression checks for rules before deployment.
- Measure rule performance with clear metrics (latency, false positives, leakage, precision).
- Partner with data scientists to integrate ML-based risk scores, anomaly detectors, or velocity-based models into the rule engine.
- Define how risk signals are weighted, aggregated, or combined with deterministic rules.
- Ensure models and rules work coherently within the monitoring architecture.
- Work closely with platform and backend engineers to improve system reliability and automation for real-time alert pipelines, rule execution framework, data ingestion & streaming, audit logs & version control, and monitoring dashboards.
- Define data requirements for fraud/AML systems: event mapping, attributes, enrichment.
- Lead investigations into data discrepancies and improvements to event quality.
- Partner with data engineering to ensure the pipeline is fit for detection logic.
- Manage a small team of technical analysts responsible for rules design and monitoring logic.
- Work with the Head of First Line Risk to prioritise work and align on roadmap.
- Build a strong engineering mindset in the fraud monitoring team: documentation, testing, performance measurement.
What We're Looking For
- 6+ years in fraud/risk engineering, data engineering for fraud, or technical fraud/risk analytics.
- Hands-on experience designing or maintaining fraud/AML rules engines, transaction monitoring systems, or risk scoring pipelines.
- Strong SQL skills and familiarity with distributed data systems (Snowflake, BigQuery, Redshift, or similar).
- Understanding of event-driven architectures, stream processing, and real-time detection (Kafka, Pub/Sub, Flink, etc.).
- Ability to work with engineering teams on API flows, backend logic, and alerting infrastructure.
- Deep understanding of fraud typologies (card fraud, account takeover, mule activity, merchant fraud, synthetic IDs).
- Good understanding of AML detection logic (structuring, layering, suspicious patterns, velocity signals).
- Experience interpreting model outputs and integrating risk signals into systems.
- Experience managing technical teams (analysts, engineers, or hybrid profiles).
- Ability to convert complex detection problems into clear engineering requirements.
- Strong communication skills for working with engineers, data scientists, and risk leadership.
Nice to Have
- Experience with fraud/risk platforms (Feedzai, Featurespace, Ravelin, Actimize, Alloy).
- Familiarity with microservices architecture and rule evaluation engines.
- Python experience for data analysis or prototype rule testing.
- Prior experience in merchant acquiring, high-velocity payments, or embedded finance.
Technical Stack
- SQL, Snowflake, BigQuery, Redshift
- Kafka, Pub/Sub, Flink
- Python
Team & Environment
You will manage a small team of technical analysts and work closely with Data Engineering, Risk Analytics, Product, Data Science, and Platform Engineering. You will partner with the Head of First Line Risk.
Benefits & Compensation
- Flexible working hours
- Health Insurance
- Physical and mental health support through partnership with MyFitness
- 25 days of Annual leave (+ Bank Holidays)
- Possibility to visit other Teya offices
- Friday lunch in the office
- Friendly, comfortable and high-end work equipment and informal office environment
- Hybrid work mode policy
Work Mode
This role follows a hybrid work mode policy.
Teya is proud to be an equal opportunity employer. We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work.
