Jobs at SambaNova Systems

Support three senior leaders across Engineering, G&A, and Sales by managing complex calendars, meetings, travel, expenses, communications, events, action items, vendors, and confidential information. Coordinate cross-functional processes, track follow-ups and OKRs, assist with organizational planning, and support ad hoc projects in a fast-paced technology environment.

Lead regional technical customer support for SambaNova’s AI infrastructure products, including SambaRack, SambaStack, and SambaCloud. Provide whole-stack troubleshooting, debug machine learning models, mentor support engineers, improve support processes, create documentation, test new features, and coordinate with engineering, site reliability, and field service teams. The role also involves customer relationship management, Jira-based engineering feedback, and participation in on-call rotations.

As a Software Architect, you will define the SambaStack platform's technical direction, ensure system scalability, and resolve architectural challenges while mentoring engineers.

Owns architecture, microarchitecture, RTL design, integration, and implementation of high-speed I/O and memory subsystems for AI accelerator platforms. Responsibilities include SystemVerilog development, front-end design flows, protocol and vendor IP integration, PPA optimization, timing closure, verification collaboration, issue resolution, and cross-functional lifecycle execution from architecture through silicon.

Designs, builds, and deploys production generative AI applications for strategic enterprise customers using SambaNova hardware and software. Responsibilities include architecting RAG and multi-agent workflows, optimizing inference performance, troubleshooting across model, software, and hardware layers, translating customer needs into product requirements, supporting technical sales engagements, creating reusable deployment accelerators, and presenting technical findings to customers and internal teams.

Leads ecosystem strategy for SambaNova’s AI accelerator products across networking, inference serving, storage, caching, prefill, CPU offload, and compiler systems. Defines build-versus-partner decisions, owns reference architectures and certification programs, drives co-optimization with software and model partners, and converts ecosystem relationships into deployments, demand, and revenue. The role also leads external positioning, analyst engagement, executive scorecards, and cross-functional execution with engineering, product strategy, marketing, and partners.

Leads competitive intelligence and product strategy for AI accelerator infrastructure. Builds TCO, tokenomics, capacity, and demand models; tracks competitor architectures, roadmaps, supply signals, and data-center systems; translates findings into roadmap, pricing, positioning, and investment decisions. Develops agentic AI tooling to automate research monitoring, specification extraction, and executive briefings. Runs weekly, monthly, and quarterly intelligence cadences for product and executive stakeholders.

Owns product lifecycle and configuration management for complex AI infrastructure and semiconductor hardware products. Administers and configures the enterprise PLM platform, workflows, access controls, integrations, reports, and release processes. Chairs change control boards, manages configuration baselines through NPI gates, controls engineering changes and product data, and drives cross-functional decisions across engineering, manufacturing, supply chain, quality, and external partners. Also owns PLM program deliverables, audits, governance, training, and continuous improvement.

Design and implement runtime-stack features for scalable, high-performance ML inference and training. Develop system software, drivers, kernels, user-space libraries, management tools, profiling and debugging capabilities. Optimize hardware utilization and performance across distributed systems, collaborate with hardware, compiler, ML application, and DevOps teams, and build, test, and deploy software for AI and HPC platforms.

Lead SambaNova’s EMEIA sales organization and regional go-to-market strategy across Europe, the Middle East, India, and Africa. Build and coach sub-regional leadership and sales teams, execute product launches, establish repeatable sales methodologies, improve forecasting and pipeline discipline, support strategic enterprise deals, and develop C-level relationships. Partner cross-functionally with operations, marketing, product, customer success, and partnerships teams to drive predictable revenue growth across enterprise, government, neo-cloud, and model-maker segments.

Own full lifecycle recruiting for semiconductor hardware engineering roles, including design verification, ASIC/RTL design, physical design, and PCB/systems engineering. Partner with hiring managers to define roles, build pipelines, design interviews, source passive silicon talent, coordinate feedback, close candidates, and maintain recruiting data and metrics in Greenhouse.

Drive planning and execution of multiple software and ML workstreams, manage cross-functional dependencies, gather requirements, track schedules, support development-to-deployment, and improve processes to deliver customer product releases.

Develop and enhance runtime stack features for high performance ML applications, manage system software, and collaborate with teams to optimize AI systems.

Lead development and optimization of the compiler stack for ML systems, collaborate across teams, integrate and deploy products, map ML operations to hardware, and drive compiler infrastructure innovation and performance debugging.

The role involves leading a software engineering team focused on AI infrastructure and enterprise software, ensuring technical quality and team development while also contributing as a hands-on engineer.

Build and improve software for SambaRack, a rack-scale AI infrastructure platform. Responsibilities include developing hardware management, monitoring, control, diagnostics, telemetry, observability, and infrastructure services; improving performance, reliability, and scalability; integrating software with hardware; resolving bottlenecks; and collaborating with hardware, DevOps, QA, and product teams. The role supports production, enterprise, customer-managed, and air-gapped deployments.

Design and build reliable software for SambaRack, a rack-scale AI infrastructure platform. Responsibilities include hardware control, monitoring, diagnostics, telemetry, observability, distributed systems, and hardware-software integration. The role improves system performance, scalability, and reliability; leads technical architecture; resolves systemic risks; collaborates across engineering teams; and mentors engineers supporting enterprise and air-gapped deployments.

Define and own the end-to-end architecture of SambaStack, an enterprise AI inference platform. Set technical strategy and standards across engineering teams, lead design reviews, resolve scalability and reliability risks, and guide platform evolution. Partner with ML, product, QA, and DevOps teams to make architectural decisions, evaluate emerging technologies, mentor engineers, and design systems for production-scale AI inference workloads.

Design and own the architecture of SambaRack’s infrastructure and management platform for rack-scale AI systems. Lead hardware-software integration, control, monitoring, diagnostics, observability, reliability, and scalability efforts. Establish architectural standards, guide technical direction, resolve systemic risks, and collaborate with Hardware Engineering, DevOps, QA, and Product teams. Mentor engineers and evaluate technologies for enterprise, production, customer-managed, and air-gapped deployments.

Lead development of SambaNova’s enterprise AI inference serving platform. Responsibilities include improving performance, scalability, reliability, and platform capabilities; designing backend components for AI inference; building testing frameworks and automation; solving distributed-systems challenges; and driving technical execution and software quality across cross-functional engineering initiatives.