Forward Deployment Engineer

The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale.

SambaNova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets.

About SambaNova

Join the company that's building the future of AI computing. SambaNova is disrupting the AI and high-performance computing space with an integrated hardware and software platform.

Our SambaStack inference serving platform is pushing the boundaries of inference serving for generative AI and large language models. We are a team of passionate innovators tackling some of the world's most challenging computational problems. We help enterprises and service providers host their own AI inference platforms, powered by our state-of-the-art RDU (Reconfigurable Dataflow Unit) hardware architecture. Our cloud-agnostic, enterprise-grade inference serving platform enables seamless deployment, management, and scaling of foundation model workloads at production scale.

SambaNova is hiring a Forward Deployed Engineer (FDE) for our SambaStack based product portfolio in our Customer Success Organization.

Responsibilities:

• Embed directly with strategic enterprise customers to design, build, and deploy production GenAI applications on SambaNova's SN40L platform and SambaStack based product portfolio
• Architect and implement LLM-powered workflows — including RAG pipelines, multi-agent systems, fine-tuning workflows, and coding solutions — tailored to each customer's data, infrastructure, and business goals.
• Optimize AI inference performance on SambaNova hardware; benchmark model throughput, latency, and accuracy against customer requirements and competitor baselines.
• Troubleshoot and resolve production issues end-to-end across model, software, and hardware layers — acting as the first and last line of technical escalation in the field.
• Translate customer needs into clear product requirements and engineering feedback; serve as the primary voice of field reality to SambaNova's Product and Engineering teams.
• Partner with Account Executives and Solutions Engineers to shape technical sales strategy, scope engagements, and demonstrate platform differentiation during evaluations and proof-of-concepts.
• Develop reusable accelerators, reference architectures, and internal playbooks that scale learnings from one deployment to many.
• Present technical findings, architecture decisions, and roadmap input at customer executive briefings and internal forums; represent SambaNova at industry conferences and events.

Qualifications:

• 5+ years of hands-on engineering experience, with a strong record of shipping production AI/ML systems.
• Deep expertise in GenAI application development: LLM orchestration, RAG, agentic frameworks (LangChain, LlamaIndex, DSPy), prompt engineering, and evaluation pipelines.
• Strong foundations in ML fundamentals — model training, fine-tuning, inference optimization, quantization, and performance benchmarking.
• Proficiency in Python (required); working knowledge of C++ or CUDA a strong plus for hardware-layer debugging.
• Experience deploying AI workloads on cloud infrastructure (AWS, Azure, GCP) and familiarity with containerization, orchestration (Kubernetes, Docker), and MLOps tooling.
• Comfortable engaging directly with customers: able to run technical discovery, set expectations, push back constructively, and present to executive and practitioner audiences alike.
• Bachelor's or graduate degree in Computer Science, Electrical Engineering, Mathematics, Physics, or equivalent practical experience.
• Willingness to travel up to 50% to customer sites — flexible based on engagement needs.

Bonus qualifications:

• Experience with AI accelerators or custom silicon (TPUs etc.)
• CUDA / low-level GPU programming
• Familiarity with VLLM / SGLang
• Enterprise AI deployments in regulated industries