Jobs at SambaNova Systems

Embed with enterprise customers to design, build, and deploy production GenAI applications on SambaNova hardware and SambaStack. Architect LLM workflows (RAG, agents, fine-tuning), optimize inference performance, troubleshoot across model/software/hardware layers, drive product feedback, support sales evaluations/POCs, and create reusable reference architectures and playbooks.

Embed with enterprise customers to design, build, and deploy production generative AI applications on SambaNova hardware and SambaStack. Architect LLM workflows (RAG, agents, fine-tuning), optimize inference performance, troubleshoot across model/software/hardware layers, translate field needs to product teams, support technical sales and POCs, develop reusable reference architectures, and present results to customers and internal stakeholders.

Own and operate a global AI inferencing platform: ensure uptime, low-latency performance, scalability and cost efficiency. Build monitoring, alerting, CI/CD, IaC, autoscaling, capacity planning, incident response, and participate in a shared on-call rotation to maintain 24/7 service reliability.

Serve as the primary post-sales partner for enterprise accounts, leading onboarding, adoption monitoring, mitigation of churn risk, and expansion. Build tailored success plans, coordinate cross-functional delivery, deliver executive business reviews, drive upsell/cross-sell, and relay customer feedback to Product and Engineering.

The Principal Compiler Engineer will lead compiler engineering, optimizing ML model performance and coordinating with development teams to innovate compiler infrastructure.

As a Senior Cloud SRE, you'll ensure the reliability and performance of our AI inferencing service, handle incident management, and optimize cloud infrastructure and resource utilization.

Own post-sales relationships for enterprise accounts, guide onboarding to full-scale AI deployment, build tailored success plans, monitor adoption, mitigate churn, drive upsell/cross-sell, deliver executive business reviews, and relay customer feedback to Product and Engineering.

The ML Features Solutions Engineer will develop, optimize, and deploy core machine learning features for enterprise applications while collaborating with cross-functional teams to ensure production-grade quality and performance.

Lead technical accounting and general ledger functions, own US GAAP policy and close process, advise on complex transactions (revenue, leases, equity, M&A), manage SOX controls and external audits, drive process automation, and build a scalable accounting team while partnering with Finance, Legal, Tax, and business stakeholders.

The Technical Program Manager will lead software programs, collaborate with multiple teams, manage dependencies, and drive product delivery to improve engineering velocity and transparency.

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.

Own AI Cloud strategy and roadmap to showcase hardware advantages, define served models and pricing/tokenomics, write technical PRDs, drive cloud features for enterprise inference, incubate solution architectures, and align product with sales and partner motions to accelerate deals.

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

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 Supply Chain Specialist manages inventory, tracks supply demand, issues POs, and collaborates with manufacturing partners to support operations and ensure product delivery.

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.

Own reliability, performance, and scalability of a cloud AI inferencing service. Participate in shared on-call rotation, build monitoring/alerting, implement IaC, automate CI/CD, optimize performance and capacity, define SLOs/SLIs, and support multi-region deployments (cloud and on-prem).

Define and own networking architecture for next-generation super-pod ML hardware. Lead R&D, specify high-performance networking fabrics, drive ML networking roadmap, collaborate cross-functionally across silicon, systems, and software, contribute to industry standards, and deliver performant, reliable, and secure interconnect solutions at scale.

Create technical messaging, demos, collateral, and enablement for AI infrastructure and inference use cases. Translate hardware and architecture details into customer- and field-facing materials, support launches and benchmarking, and partner with product, engineering, sales, and field teams to refine positioning and technical proof points.