Forward Deployment Engineer

Join SambaNova, a leading AI company, as a Forward Deployed Engineer. In this role, you will work directly with strategic enterprise customers to design, build, and deploy production GenAI applications. You will optimize AI inference performance, troubleshoot production issues, and translate customer needs into product requirements. Additionally, you will partner with sales teams, develop reusable accelerators, and represent SambaNova at industry events.

• Collaborer directement avec des clients stratégiques pour concevoir, construire et déployer des applications GenAI sur la plateforme SN40L de SambaNova.
• Architecturer et mettre en œuvre des flux de travail alimentés par des LLM, y compris des pipelines RAG, des systèmes multi-agents et des workflows de fine-tuning.
• Optimiser les performances d'inférence de l'IA sur le matériel de SambaNova, en benchmarkant le débit, la latence et la précision des modèles.
• Willingness to travel up to 50% to customer sites — flexible based on engagement needs
• Bachelor's or graduate degree in Computer Science, Electrical Engineering, Mathematics, Physics, or equivalent practical experience
• 5+ years of hands-on engineering experience, with a strong record of shipping production AI/ML systems
• Comfortable engaging directly with customers: able to run technical discovery, set expectations, push back constructively, and present to executive and practitioner audiences alike
• Experience deploying AI workloads on cloud infrastructure (AWS, Azure, GCP) and familiarity with containerization, orchestration (Kubernetes, Docker), and MLOps tooling
• Proficiency in Python (required); working knowledge of C++ or CUDA a strong plus for hardware-layer debugging
• Strong foundations in ML fundamentals — model training, fine-tuning, inference optimization, quantization, and performance benchmarking
• Deep expertise in GenAI application development: LLM orchestration, RAG, agentic frameworks (LangChain, LlamaIndex, DSPy), prompt engineering, and evaluation pipelines
• Enterprise AI deployments in regulated industries
• Familiarity with VLLM / SGLang
• CUDA / low-level GPU programming
• Experience with AI accelerators or custom silicon (TPUs etc.)