Lead Engineer

Role Overview

We are seeking a Lead Engineer for our Trading Pricing Engine team. This is a full-time remote position designed for an experienced backend engineer ready to own the architecture of high-performance trading systems in dynamic, real-time environments.

Your Responsibilities:

• Arcitect and develop scalable systems implementing robust pricing algorithms with low-latency data processing.
• Ensure reliable integrations with trading platforms and external market data sources globally.
• Lead a small engineering squad by providing technical direction, conducting code reviews, and establishing best practices for performance, security, and reliability.
• Collaborate closely with product and quantitative teams to translate business requirements into elegant technical solutions.
• Monitor production systems, troubleshoot critical issues, and drive continuous improvements in system stability and accuracy.
• Mentor team members, contribute to strategic roadmaps, and participate in planning/estimation for timely feature delivery.

Qualifications:

• Domain Experience: Strong background in backend engineering for trading or financial systems. Expertise required in building low-latency, high-throughput services and real-time data processing pipelines.
• Programming Proficiency: Mastery of modern languages such as Java, Kotlin, C#, C++, Go, or Rust with solid grasp of object-oriented and functional programming concepts.
• Distributed Systems: Hands-on experience designing microservices architectures using event-driven/streaming platforms (e.g., Kafka, RabbitMQ).
• Performance Optimization: Deep understanding of data structures, algorithms, concurrency models, and techniques for profiling/tuning applications to minimize latency.
• Integration Knowledge: Experience integrating with trading platforms, market data providers, or financial APIs; familiarity with order books, price feeds, and risk constraints.
• Data & Storage: Practical skills in relational/NoSQL databases, caching strategies (Redis/Memcached), and resilient storage patterns.
• Cloud & DevOps: Exposure to AWS/GCP/Azure; proficiency with CI/CD pipelines, containerization (Docker), and orchestration tools like Kubernetes.