Forward Deployment Engineer

Role Description

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

• 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.

Requirements

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

Benefits

• Competitive total rewards package, including base salary, equity, and benefits.
• 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents.
• Health Savings Account (HSA) with employer contribution.
• Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans.
• Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care.
• Well-being benefits including a full subscription to Headspace, Gympass+ membership, One Medical membership, and counseling services with an Employee Assistance Program.