AI Solutions Engineer

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value.

We are looking for a Senior Principal AI Solutions Engineer: a hands-on technical leader who sets the technical direction for our solutions portfolio and still builds. This is someone who can go from a customer problem to a polished, working, agentic application in days, and then harden it for production. You will work across the whole modern AI stack: open-weight models, agent frameworks and tool use, self-improving evaluation loops, multimodal and voice pipelines, and the front end that makes it all usable by knowledge workers. You will lead hands-on engagements with our most strategic customers, mentor and raise the bar for the wider solutions team, and feed what you learn back into the platform. 

Responsibilities 

Build agentic and self-improving systems 

• Agentic AI Architecture: Design and build single- and multi-agent systems with planning, tool and function calling, MCP, memory, and long-running workflows that are reliable enough for production • Self-Improving Systems: Build feedback loops that make agents better over time, including automated evals, LLM-as-judge, trace-driven prompt and program optimization (e.g. DSPy-style), synthetic data generation, and fine-tuning from production signals
• Evaluation and Observability: Set up eval harnesses, tracing and guardrails so customers can measure quality, cost and latency, and trust what they deploy 

Get the most from open models 

• Open-Weight Model Expertise: Choose, adapt and combine open models (e.g. Llama, Qwen, DeepSeek, gpt-oss, Gemma, GLM) for customer use cases, including LoRA/PEFT fine-tuning, distillation and model routing 
• Performance and Benchmarking: Benchmark end-to-end solutions, not just tokens per second, and show where fast inference changes what an application can do 
• Model Integration: Validate new models and capabilities on SambaNova's platform stack and report gaps to Product and Engineering