Staff Replication Development Engineer

Location: Remote - North Carolina; hybrid work format

Company

hirify.global develops the Infinia AI Data Platform and its enterprise data infrastructure capabilities.

What you will do

• Lead the design and development of multi-threaded asynchronous replication systems with parallel streaming.
• Build object-level delta replication with checkpointing, resume, failure recovery, and retry capabilities.
• Develop bucket- and share-level replication controls, metadata tracking, change detection, and efficient synchronization mechanisms.
• Implement secure TLS 1.3 data transfer with mutual authentication and end-to-end checksum validation.
• Build REST APIs, RPO visibility, alerting, monitoring dashboards, and operational insights for replication health and performance.
• Provide architectural guidance and mentorship while collaborating with QA, backend, security, and platform teams on reliability and scale.

Requirements

• 8+ years of experience in distributed systems, storage systems, or backend software engineering.
• Strong programming skills in C++, Go, Java, or Rust.
• Experience designing data replication systems, data pipelines, or distributed data services.
• Deep understanding of consistency, availability, scalability, fault tolerance, multithreading, concurrency, and parallel processing.
• Knowledge of TCP/IP, HTTP/HTTPS, TLS, data integrity mechanisms, REST APIs, service-based architectures, and observability.
• Strong debugging, problem-solving, and system design skills.

Nice to have

• Experience with asynchronous replication, disaster recovery, backup systems, or object storage.
• Knowledge of delta encoding, change data capture, or incremental data synchronization.
• Experience building high-throughput, low-latency data movement systems.
• Exposure to mutual TLS, encryption, authentication, enterprise-scale data platforms, and performance optimization.

Culture & Benefits

• Hybrid work arrangement based in North Carolina.
• Collaboration with backend, security, platform, and QA engineering teams.
• Opportunity to provide technical leadership and mentorship on a large-scale AI data platform.