Staff Backend Engineer – Take Profit Trader

This is a fully remote position, open to applicants in United States.

📋 Description

• Creating and developing a real-time notification platform that provides low-latency alerts and account updates for traders and internal systems.

• Designing and managing Kafka/MSK streaming pipelines that collect live trading data from various upstream systems.

• Architecting scalable event-driven systems featuring durable messaging, replay capabilities, and optimized partitioning strategies.

• Building stateful stream processing applications that facilitate risk detection, fraud monitoring, and market integrity initiatives.

• Optimizing PostgreSQL and time-series database schemas for both operational tasks and historical analytics.

• Developing and enhancing production-ready .NET Core APIs that underpin trading, risk, and fraud systems.

• Establishing service reliability standards, alongside monitoring, alerting, and observability to guarantee highly available systems.

• Leading architectural decisions throughout the engineering organization while mentoring senior engineers and actively contributing to implementation.

• Collaborating closely with engineering leadership to define technical standards and the long-term strategy for the platform.

⛳️ Requirements

• Over 10 years of experience in backend or distributed systems engineering.

• 3 to 4+ years in a Staff Engineer, Principal Engineer, or a similar technical leadership role.

• Demonstrated experience in designing and managing high-throughput, low-latency, real-time production systems.

• Extensive hands-on experience in developing backend services and APIs using .NET Core.

• In-depth knowledge of WebSockets or similar persistent connection technologies, encompassing scaling, connection management, and delivery guarantees.

• Strong proficiency with Kafka, MSK, or analogous streaming platforms, covering topic design, partitioning, and consumer scaling.

• Experience in building stateful stream processing applications utilizing Kafka Streams, Flink, or equivalent technologies.

• Advanced skills in SQL and PostgreSQL, including replication strategies and schema optimization.

• Familiarity with time-series databases such as TimescaleDB, ClickHouse, InfluxDB, or similar technologies.

• Comprehensive understanding of distributed systems concepts, including consistency models, idempotency, fault tolerance, delivery guarantees, and backpressure.

• Experience in trading, fintech, financial services, payments, fraud detection, or risk systems is strongly preferred.

• Knowledge of AWS streaming services, infrastructure as code, or trade surveillance systems is a plus.

🏝️ Benefits

• Medical insurance

• Wellness stipend

• Paid time off

• Company holidays