Forward Deployment Engineer
New
S
SambaNova SystemsArtificial Intelligence
Remote - USFull-TimeMiddle
Salary$138,000 — $170,000 USD
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPythonKubernetesMachine LearningLLMMLOpsLangChain
Requirements
- 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
- Experience deploying AI workloads on cloud infrastructure (AWS, Azure, GCP)
- Familiarity with containerization, orchestration (Kubernetes, Docker), and MLOps tooling
- Comfortable engaging directly with customers: able to run technical discovery, set expectations, and present to executive and practitioner audiences
- 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
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
- Translate customer needs into clear product requirements and engineering feedback; serve as the primary voice of field reality
- Partner with Account Executives and Solutions Engineers to shape technical sales strategy and demonstrate platform differentiation
- Develop reusable accelerators, reference architectures, and internal playbooks
- Present technical findings, architecture decisions, and roadmap input at customer executive briefings
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