Senior Principal Engineer - SambaRack
About the team
Join the company that's building the future of AI infrastructure. SambaNova is developing advanced AI systems powered by our RDU (Reconfigurable Dataflow Unit) architecture, combining hardware and software into an integrated platform for large-scale AI deployments.
Our products include SambaRack, a rack-scale AI infrastructure system, and SambaStack, our inference serving platform. Together, they enable customers to deploy and operate production AI environments with performance, reliability, and control.
We are a team of engineers and innovators building next-generation AI infrastructure systems designed for enterprise-scale deployments.
About the role
SambaNova is hiring a Senior Principal Engineer for the SambaRack platform.
You will help design and build the software that enables customers to monitor, control, update, and diagnose SambaRack systems safely and reliably.
This is a hands-on software development role requiring significant technical expertise in systems and infrastructure, focused on building rack-scale hardware management and infrastructure software that operates in direct contact with hardware across diverse production environments, including customer-managed and air-gapped deployments.
As a Senior Principal Engineer on the SambaRack team, you will:
- Improve the performance, scalability, and reliability of rack-scale infrastructure and management software
- Introduce new features and capabilities for monitoring, control, and diagnostics of SambaRack systems
- Design and build components for hardware-software integration points across rack-scale AI systems
- Drive technical execution across critical infrastructure initiatives, tightly integrated with hardware
This is a high-impact, high-visibility role at the intersection of:
- AI infrastructure
- Distributed systems
- Hardware-software integration
Responsibilities
Some of your responsibilities will include:
- Design and build core software components that enable safe, reliable control, monitoring, and diagnostics for rack-scale AI systems
- Lead the technical design and implementation of hardware-software integration points and infrastructure services
- Improve observability, telemetry, and diagnostics capabilities across the SambaRack platform
- Proactively identify and resolve systemic risks, including performance bottlenecks, reliability gaps, and scaling constraints, before they impact customers
- Collaborate closely with Hardware Engineering, DevOps, QA, and Product teams to translate infrastructure requirements into sound technical solutions
- Contribute to and help evolve architectural standards, patterns, and best practices across the infrastructure software team
- Serve as a technical leader and mentor, fostering engineering excellence and systems-level thinking within the team
- Evaluate emerging technologies and industry trends to inform technical approach and platform direction
- Design and build new systems, components, and capabilities to solve new and interesting problems in the AI inference space
Required qualifications
- 8-12 years of software engineering experience
- Strong experience building infrastructure, systems, or platform software
- Solid programming experience in Go, Rust, Python, or C/C++
- Strong understanding of Linux, networking, concurrency, and distributed systems
- Experience designing reliable backend or control-plane services for production systems
- Experience with hardware management systems such as BMCs, Redfish, IPMI, or OpenBMC
- Experience with monitoring, telemetry, or observability systems for infrastructure platforms
- Excellent problem-solving skills and attention to detail
- Ability to collaborate across cross-functional teams
- Knowledge of software development best practices and coding standards
Preferred qualifications
- Experience with rack management, server management, or bare-metal infrastructure platforms
- Experience with Prometheus, Grafana, and metrics exporter design
- Familiarity with fleet management, diagnostics systems, and hardware health monitoring
- Experience supporting enterprise or air-gapped deployments
- Solid understanding of Kubernetes, Helm Charts, and the Kubernetes ecosystem
- Experience designing scalable infrastructure and distributed systems
- Familiarity with telemetry systems and infrastructure observability tooling
