Senior Staff Backend Engineer - Fraud Detection

Overview

Lead architecture and development of large-scale ML-powered data platforms for fraud detection, risk evaluation, and trust systems. Bridge Data Science and Engineering by building reliable, scalable infrastructure for production machine learning models.

What you'll do

• Lead architecture and development of scalable data and ML infrastructure.
• Build and optimize batch and real-time data pipelines.
• Own productionization of machine learning models.
• Translate modeling requirements into scalable engineering solutions.
• Define technical vision and roadmaps for ML platforms and fraud infrastructure.
• Lead cross-functional initiatives and establish engineering best practices.
• Mentor senior engineers and lead technical decisions during incidents and reviews.

What you'll need

• 13+ years of backend, data engineering, or distributed systems experience.
• Experience building large-scale real-time distributed data processing systems.
• Hands-on experience with Flink, Kafka, Spark Streaming, or similar technologies.
• Strong Java backend development and distributed systems architecture skills.
• Experience building low-latency, high-throughput pipelines and serving systems.
• Experience deploying and scaling ML models in production.
• Knowledge of system design, scalability, fault tolerance, and operational excellence.

Nice to have

• Experience in fraud detection, risk systems, trust and safety, payments risk, or similar domains.
• Experience with ML platforms, model serving, feature stores, or inference pipelines.
• Experience with cloud-native architectures and containerized environments.
• Experience operating systems processing millions of daily events or transactions.
• Familiarity with GenAI tools for software development and engineering productivity.

Details

• Location: Bengaluru.
• Hybrid, onsite, or remote working model stated; hybrid work generally requires at least 3 office days and allows 2 work-from-home days weekly.