Senior Principal AI Solutions Engineer - San Jose, California, United States

Originally posted 29 September 2026 by the employer.

About the role

This role is for a hands-on technical leader responsible for setting the technical direction for the solutions portfolio and building agentic applications. The work involves the full modern AI stack, from open-weight models and agent frameworks to multimodal and voice pipelines, integrating with the SambaNova platform which uses RDU (Reconfigurable Dataflow Unit) technology.

What you'll do

• Design and build single and multi-agent systems with planning, tool and function calling, MCP, memory, and long-running workflows.
• Build feedback loops for agents using automated evals, LLM-as-judge, trace-driven prompt and program optimization, synthetic data generation, and fine-tuning from production signals.
• Choose, adapt, and combine open-weight models (e.g., Llama, Qwen, DeepSeek, gpt-oss, Gemma, GLM) for customer use cases, including LoRA/PEFT fine-tuning, distillation, and model routing.
• Benchmark end-to-end solutions and validate new models and capabilities on SambaNova's platform stack.
• Build polished, usable web applications (e.g., React/Next.js, TypeScript) for knowledge workers.
• Lead technical discovery, workshops, hackathons, and hands-on co-builds with strategic customers.

What you'll need

• Bachelor's degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, Physics, Statistics, or a related field.
• 8+ years of industry experience in software, ML, or solutions engineering, including 3+ years building LLM-based applications that reached production.
• Proven experience building agentic systems: tool and function calling, multi-agent orchestration, and frameworks such as LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, or equivalent.
• Hands-on experience with open-weight models: serving, prompting, fine-tuning (LoRA/PEFT), and evaluation.
• Strong full-stack skills: expert Python plus modern front-end development (TypeScript, React/Next.js), APIs, and cloud deployment.
• Experience designing evals and benchmarks for LLM applications, covering quality, latency, and cost.
• Excellent customer communication, with the ability to lead workshops and explain architecture to both executives and engineers.
• A track record of technical leadership across teams: setting architecture direction, mentoring senior engineers, and owning outcomes for strategic accounts.

Nice to have

• Experience building self-improving or learning systems: prompt/program optimization, RL from feedback, synthetic data pipelines, or continual fine-tuning.
• Experience building real-time voice agents (e.g., LiveKit, Pipecat, WebRTC) and working with speech models (ASR/TTS).
• Experience with multimodal and vision-language models and document-understanding pipelines.
• Domain experience in financial services, legal, healthcare, public sector, or scientific research.
• Familiarity with inference frameworks (vLLM, SGLang, TensorRT-LLM) and hardware-aware performance tuning.
• Experience with MCP, RAG at enterprise scale, and agent security and guardrails.
• Open-source contributions, public demos, or technical content in the AI community.

Skills: agentic AI, LLM, fine-tuning, SambaNova platform, full-stack