Senior RAD developer - Python & Java
Overview:
In this role you will architect and deliver high-performance backend systems for real-time data and risk analytics. You will design event-driven, low-latency pipelines using Java and Kafka, and build scalable microservices that process streaming data on AWS with Kubernetes. You will champion reliability, observability, and CI/CD while exploring AI-enhanced software development to accelerate delivery. You'll work on platforms supporting risk, margin, and exposure monitoring in a multi-region, data-driven environment. This opportunity combines deep engineering, financial-domain impact, and modern cloud-native practices to shape real-time decision-making. Compensation / Benefitsmedical coveragedental coveragevision coveragepaid leaveflexible work arrangementsequal opportunity employer
Responsibilities:
- Design and develop low-latency, high-throughput backend systems using Java
- Implement event-driven architectures leveraging Kafka and related messaging tech
- Build and optimize real-time data pipelines with Kafka Streams and schema management
- Design distributed systems and microservices with performance tuning and caching strategies (Redis)
- Develop platforms for risk analytics, margin calculations, and exposure monitoring
- Collaborate on cloud-native development with AWS, containers, and Kubernetes
- Ensure high availability, multi-region resilience, and scalable real-time workloads
- Establish CI/CD, DevSecOps, observability, and data-driven engineering metrics
- Contribute to automated testing and quality engineering for production-grade reliability
- Explore AI/ML-driven applications for predictive analytics and anomaly detection
Key requirements:
- Proficiency in Java and Python for real-time streaming workloads
- Extensive experience with Kafka ecosystem (producers, consumers, topics, Kafka Streams)
- Knowledge of event ordering, partitioning, replay, idempotency, fault tolerance, delivery semantics
- Experience designing distributed systems and microservices; caching with RedisCloud experience (AWS); containerization and Kubernetes
- Ability to design multi-region, highly available architectures
- Familiarity with risk analytics or time-sensitive financial computations
- Exposure to AI/ML-driven applications and predictive analyticsstrong problem-solving and analytical abilitiescollaboration and cross-functional communicationdata-driven decision making
JavaPythonKafka