Senior backend engineer building services for real-time risk assessment and fraud detection at a fintech, including data pipelines over large transaction volumes and internal tools for risk teams. Core stack is Go or Python with MySQL, Redis, Kafka, and Elasticsearch; on-site in Singapore.
About the Company
Our client is a fast-growing technology company in the financial services / FinTech space, building scalable digital platforms and risk infrastructure to support secure, real-time transactions and business operations.
The role is well suited for engineers who enjoy working on distributed systems, real-time data processing, payments, fraud detection, or financial technology platforms.
What You'll Work On
Build and maintain backend services supporting real-time risk assessment and fraud detection.
Develop scalable services for executing risk rules, calculations, and automated decision-making.
Design data pipelines that collect, process, and transform large volumes of transactional and behavioural data.
Develop internal systems that allow risk teams to configure, test, and manage risk strategies efficiently.
Improve service performance with a strong focus on availability, throughput, and low latency.
Work with engineering, product, data, and risk teams to translate business requirements into reliable technical solutions.
Investigate production issues, improve monitoring, and strengthen overall platform stability.
Contribute to architecture discussions, engineering standards, and continuous system improvements.
What We're Looking For
Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, FinTech, or a related discipline.
At least 5 year of backend software engineering experience.
Strong development skills in Go, Python, or another modern backend language.
Practical experience with common backend technologies such as MySQL, Redis, Kafka, and Elasticsearch.
Solid understanding of APIs, databases, asynchronous processing, and backend system design.
Strong analytical and troubleshooting skills.
Comfortable working with multiple teams and solving problems in a fast-moving environment.
Good to Have
Previous experience in payments, digital banking, fintech, fraud prevention, or risk management platforms.
Experience with streaming or big-data technologies such as Flink, Spark, Hadoop, or Kafka-based processing systems.
Knowledge of real-time decision engines, configurable rule platforms, or fraud detection workflows.
Experience working with high-volume transactional systems or distributed architectures.
Exposure to data modelling, statistical methods, or machine learning applications related to risk.
Experience supporting business or risk teams with technical tools and data-driven decision systems.