Software Engineer - Network Observability

We are seeking an experienced Senior Software Engineer to contribute to the architecture, development, and scaling of a high-performance network monitoring and observability platform. This role will focus on building systems that provide deep visibility into RDMA, RoCE, InfiniBand, and TCP/IP networks. The ideal candidate has strong experience in distributed systems, Linux networking, and modern observability stacks (e.g., Grafana/Prometheus)., * Design, develop, and scale high-performance network monitoring platforms for RDMA, RoCE, InfiniBand, and TCP/IP infrastructure.

• Build backend telemetry services, observability dashboards, alerts, diagnostics, anomaly detection, SLA monitoring, and traffic analysis workflows.
• Troubleshoot complex production issues across application, OS, server, RDMA, and network layers while optimizing low-latency collection, aggregation, and alerting.
• Collaborate with cross-functional teams to deliver scalable solutions, improve engineering practices, automate operational workflows, and contribute to the technical direction of the platform.

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
• Strong hands-on programming experience in C++, Go, Python, Rust, or similar systems programming languages.
• Proven experience delivering complex infrastructure projects and contributing to the design and implementation of distributed systems.
• Experience building distributed systems, backend services, telemetry pipelines, or observability platforms.
• Hands-on experience with RDMA, RoCE, InfiniBand, or other high-performance network fabrics.
• Familiarity with libibverbs, RDMA verbs, RDMA CM, queue pairs, completion queues, memory registration, and related RDMA concepts.
• Strong knowledge of Linux networking, TCP/IP, DNS, HTTP, routing, MTU, congestion control, packet loss, latency, and performance tuning.
• Experience with traceroute-style diagnostics, path discovery, network reachability checks, synthetic probes, or active network measurements.
• Experience with monitoring and visualization platforms such as Prometheus, Grafana, Datadog, Splunk, OpenTelemetry, or similar tools.
• Strong debugging skills across software, operating system, server, and network layers.
• Experience operating production systems in Linux-based environments.
• Strong technical judgment and ability to build reliable, scalable, and maintainable systems., * Experience supporting AI/ML, HPC, storage, or GPU cluster infrastructure workloads.
• Experience with large-scale RoCE or InfiniBand deployments.
• Experience with NCCL, distributed training infrastructure, or AI cluster diagnostics.
• Experience with eBPF, XDP, DPDK, perf, tcpdump, Wireshark, ethtool, iproute2, rdma-core, or Linux kernel networking tools.
• Experience with cloud infrastructure on AWS, GCP, or Azure.
• Experience with Kubernetes, service discovery, configuration management, and infrastructure automation.
• Knowledge of security, compliance, and infrastructure best practices.
• Experience designing time-series data systems, alerting pipelines, or high-cardinality telemetry platforms.

• Challenging projects.
• A friendly and inclusive workplace culture.
• Competitive compensation.
• A great benefits package.
• Catered lunch.

Compensation for this position will vary based on the skills and experience you bring, as well as internal equity considerations. For candidates hired at the posted level, the expected base salary range is $140,000 - $210,000. The offered compensation package may also include stock options or other equity awards, subject to Clockwork’s equity program and applicable approvals. In addition to cash compensation, this role is eligible to participate in the company’s equity program, which may include stock options granted in accordance with the company’s equity plan and subject to approval and applicable vesting schedules.

Clockwork Systems was founded by Stanford researchers and veteran systems engineers who share a vision for redefining the foundations of distributed computing. As AI workloads grow increasingly complex, traditional infrastructure struggles to meet the demands of performance, reliability, and precise coordination. Clockwork is pioneering a software-driven approach to AI fabrics by delivering cross-stack observability to catch and quickly resolve problems, workload fault tolerance to keep jobs running through failures, and performance acceleration that dynamically routes and paces traffic to avoid congestion.