Quantitative Developer

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Our mission is to deliver results for our investors.

The Team

The Information Technology organization supports a flexible, scalable technology environment and advanced proprietary systems. This team builds and operates C++ backend services for Millennium's real-time risk and P&L platform, a distributed system of microservices running on AWS/Kubernetes, processing large-scale financial data with strict latency requirements. The team works on production services running 24/5, collaborating with quantitative developers, platform engineers, and business stakeholders.

What You'll Do

• Design, build, and operate high-performance C++ services for real-time pricing, risk, and P&L across fixed income and credit instruments.
• Own service reliability end-to-end: monitoring, alerting, incident response, and root cause analysis in a live production environment.
• Write thread-safe, exception-safe C++ code for concurrent, near-real-time workloads with hard latency targets.
• Optimize service performance: profiling hotspots, reducing memory allocations, improving cache behavior, and tuning throughput.
• Integrate C++ services with upstream and downstream systems via Kafka, Protobuf, and internal APIs.
• Contribute to the CI/CD pipeline: automated regression testing, A/B deployment, and blue/green release management.
• Promote engineering best practices: code review, RAII patterns, and robust error handling in a multi-threaded environment.

Requirements & Tech Stack

• Bachelor's degree in Computer Science, Software Engineering, or a related discipline.
• Up to 5 years of professional experience in C++ service/systems development.
• Strong hands-on experience in modern C++ (C++17/C++20): move semantics, smart pointers, RAII, templates, constexpr.
• Solid understanding of multithreading and concurrency: mutexes, atomics, lock-free structures, thread pools, and race condition debugging.
• Experience building and operating long-running backend services.
• Familiarity with service-oriented architecture, message queues (Kafka or similar), and serialization frameworks (Protobuf, FlatBuffers).
• Proficiency with Linux, GDB/LLDB, profiling tools (perf, Valgrind, AddressSanitizer), and CI/CD pipelines.
• Strong analytical and troubleshooting skills.
• Ideal experience with reactive or event-driven programming patterns, containerized deployments (Docker, Kubernetes), and/or exposure to financial services, pricing models, or risk systems.