Remote job
Software Engineer
Job details
About this role
Role overview
Build the distributed systems and backend infrastructure that power production AI capabilities at global scale. This systems-focused role connects machine-learning research with dependable engineering by supporting document processing, model serving, data orchestration, autonomous-agent workflows, retrieval systems, and model optimization.
Responsibilities
- Develop and maintain high-performance distributed systems for large-scale model inference and data processing. - Design horizontally scalable backend services for high-throughput data and model interactions. - Build model-serving and inference runtimes that improve resource utilization and reduce latency. - Create resilient ingestion and processing pipelines for massive datasets while preserving data integrity, tenant isolation, and availability. - Diagnose bottlenecks and improve system performance through advanced monitoring and clearly defined SLOs and SLAs.
Requirements
- At least five years of software-engineering experience focused on distributed systems and scalable backend architecture. - Experience building, deploying, and maintaining machine-learning models in high-traffic production environments. - Strong Python skills plus professional experience with a strongly typed language such as Java, Go, or C#. - Experience with container orchestration, messaging systems, and high-performance database design. - Background delivering production systems with demanding uptime and latency requirements. - Bachelor’s or master’s degree in computer science or a related technical field.
Nice to have
- Experience with stateful workflow engines or distributed task queues for complex multi-step AI processes. - Familiarity with frameworks for horizontally scaling compute-intensive machine-learning workloads, such as Ray or Spark. - Expertise in Azure or Google Cloud identity, security, and compliant networking. - Experience building platform services for large-language-model orchestration, retrieval-augmented generation, and prompt-configuration layers.
Benefits and work setup
- Hybrid arrangement with office access and an expected minimum of two in-office days per week, subject to team requirements.