Job description

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 Ship full-stack vertical solutions Front-End and Product Build: Build polished, usable web applications (e.g. React/Next.js, TypeScript) that non-technical knowledge workers can adopt, not just notebooks and APIs Vertical Knowledge Work: Build domain solutions for areas such as financial services, legal, healthcare, public sector and research: document analysis, research agents, RAG and knowledge assistants, report generation and workflow automation Multimodal Solutions: Build vision-language and document-understanding pipelines (OCR, charts, forms, images, video) combined with agentic reasoning Audio and Voice: Build real-time voice agents and audio pipelines (ASR, TTS, speech-to-speech, streaming and turn-taking) where low latency is the product Lead with customers and shape the platform Solutions Technical Strategy: Set the technical direction for the solutions portfolio: which agentic, multimodal and vertical patterns we invest in, the shared frameworks and components we build, and the engineering standards they meet Technical Leadership and Mentorship: Act as the senior technical authority across solutions engineering; review designs, mentor engineers and lift the quality of everything the team ships Executive Engagement: Act as the trusted technical advisor to customer CTOs and AI leaders on architecture, build-versus-buy and scaling AI across the enterprise Customer Engagement: Lead technical discovery, workshops, hackathons and hands-on co-builds with strategic customers, from prototype to production Reference Architectures: Publish reference architectures, starter kits, open-source examples and best-practice guides that scale beyond each engagement SambaStack Tooling: Develop tooling and automation for SambaStack deployment, management and integration Product Feedback: Feed what you learn in the field (model requests, feature gaps, developer experience) into the model roadmap and platform priorities Thought Leadership: Represent SambaNova through demos, talks, blogs and community contributions Requirements Required Qualifications Bachelor's degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, Physics, Statistics or a related field 8+ years (IC5) or 10+ years (IC6) 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 Preferred Qualifications 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 one or more knowledge-work verticals (financial services, legal, healthcare, public sector, 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 Base Salary Range: Base Pay Range $234,000 — $286,000 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

Requirements

Must-haves

Build agentic and self-improving systems
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
Ship full-stack vertical solutions
Front-End and Product Build: Build polished, usable web applications (e.g. React/Next.js, TypeScript) that non-technical knowledge workers can adopt, not just notebooks and APIs
Multimodal Solutions: Build vision-language and document-understanding pipelines (OCR, charts, forms, images, video) combined with agentic reasoning
Audio and Voice: Build real-time voice agents and audio pipelines (ASR, TTS, speech-to-speech, streaming and turn-taking) where low latency is the product
Lead with customers and shape the platform
Technical Leadership and Mentorship: Act as the senior technical authority across solutions engineering; review designs, mentor engineers and lift the quality of everything the team ships
Executive Engagement: Act as the trusted technical advisor to customer CTOs and AI leaders on architecture, build-versus-buy and scaling AI across the enterprise
Customer Engagement: Lead technical discovery, workshops, hackathons and hands-on co-builds with strategic customers, from prototype to production
Reference Architectures: Publish reference architectures, starter kits, open-source examples and best-practice guides that scale beyond each engagement
SambaStack Tooling: Develop tooling and automation for SambaStack deployment, management and integration
Product Feedback: Feed what you learn in the field (model requests, feature gaps, developer experience) into the model roadmap and platform priorities
Thought Leadership: Represent SambaNova through demos, talks, blogs and community contributions
Bachelor's degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, Physics, Statistics or a related field
8+ years (IC5) or 10+ years (IC6) of industry experience in software, ML or solutions engineering, including 3+ years building LLM-based applications that reached production

Nice-to-haves

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)
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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigollmreactnext.jstypescriptmlpython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision