Senior Distributed Systems Engineer / Architect

RapidFort is a Series A cybersecurity company focused on container and software supply-chain security. They are seeking a Senior Distributed Systems Engineer / Architect to design and build scalable custom systems for processing large volumes of data, requiring strong skills in systems thinking, algorithm design, and performance optimization.

Responsibilities:

• Design and implement scalable distributed systems that handle heavy CPU, disk, and network workloads
• Architect systems for high throughput, reliability, and efficient resource utilization
• Develop distributed algorithms and data processing pipelines
• Analyze system behavior to identify bottlenecks across compute, storage, and network layers
• Optimize workloads for maximum efficiency and minimal resource waste
• Develop strategies for parallelization, batching, and workload scheduling
• Implement system components and tooling primarily in Python and Bash
• Build custom orchestration, automation, and distributed job execution mechanisms
• Write efficient algorithms and low-level logic to manage large-scale workloads
• Build instrumentation, metrics, and telemetry to measure system performance
• Develop dashboards and analysis workflows to guide optimization decisions
• Use empirical data and experimentation to improve system behavior
• Design systems that operate reliably across distributed environments
• Implement monitoring, debugging, and recovery mechanisms for large-scale systems
• Collaborate with infrastructure and platform teams to ensure smooth deployment and operation

Requirements:

• Strong experience building distributed systems or large-scale backend infrastructure
• Deep understanding of systems performance (CPU, memory, disk I/O, networking)
• Experience optimizing workloads for throughput and efficiency
• Strong Python development skills
• Strong Bash / shell scripting
• Ability to implement and reason about algorithms and system-level logic
• Experience with parallel processing, distributed job execution, or large data pipelines
• Familiarity with Linux systems, resource scheduling, and performance tuning
• Understanding of networked systems and distributed coordination
• Strong data-driven mindset with focus on measurement and experimentation
• Experience building observability, metrics, and instrumentation
• Ability to debug complex systems in production environments
• Experience with high-performance computing (HPC) workloads
• Experience with containerized environments (Docker/Kubernetes)
• Background in large-scale data processing or distributed compute frameworks
• Familiarity with performance profiling tools and system tracing