3 days ago
Remote, United Kingdom +5 moreSenior
Responsibilities
- Lead technical discovery with AI application wrapper partners regarding product architecture, agent topology, and orchestration models.
- Build reference architectures integrating NVIDIA NIM, Nemotron, model routing, Dynamo, NeMo, AI-Q, CUDA-X libraries, OpenShell, and NemoClaw.
- Develop hands-on proofs of concept demonstrating specialized, enterprise-ready agent platforms.
- Create local agent demos, secure sandboxed workflows, developer playbooks, pilot environments, and benchmarks using DGX Spark.
- Standardize NIM and Dynamo serving patterns for agentic applications and optimize latency, throughput, retrieval quality, cost efficiency, and GPU utilization.
- Help partners implement sandboxing, policy enforcement, human-in-the-loop controls, and deployment paths across local, on-prem, sovereign, hybrid cloud, and AI Factory environments.
- Develop reusable reference architectures, workshop content, benchmark reports, and enablement playbooks.
Requirements
- BS, MS, PhD, or equivalent practical experience in Computer Science, Electrical or Computer Engineering, Physics, Mathematics, or a related engineering field.
- 8+ years of experience building, deploying, or supporting production LLM or agentic AI systems.
- Strong Python programming and practical proficiency with TypeScript or JavaScript.
- Practical knowledge of orchestration frameworks, agent frameworks, RAG platforms, workflow automation systems, or AI application builders.
- Familiarity with model serving and inference optimization, including NIM and Dynamo.
- Experience with Kubernetes, Helm, containers, and GPU-backed workloads in cloud, hybrid, or on-premises environments.
- Ability to debug application code, APIs, model endpoints, orchestration layers, retrieval systems, infrastructure, and security controls.
- Experience working directly with customers in architectural roles and influencing technical creators and corporate decision-makers.
- Preferred experience with NVIDIA NIM, Nemotron, NeMo, Dynamo, AI-Q, OpenShell, NemoClaw, NVIDIA AI Enterprise, Lovable, n8n, Haystack, LangChain, LlamaIndex, AutoGen, CrewAI, MCP-based systems, secure agent runtimes, sandboxing, tool permissioning, confidential computing, policy-as-code, enterprise governance, DGX Spark, sovereign AI, regulated enterprises, or private/on-premises deployments.
Tech Stack
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.