Senior Solution Engineer

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.   The Lambda Cloud GTM team powers our growth by enabling customers to realize their business goals with AI infrastructure. We partner with leading AI researchers and enterprise engineering teams to design, scale, and optimize high-performance GPU cloud solutions. Driven by technical mastery, agility, and a customer-first mindset, our team turns massive compute challenges into seamless, production-ready AI infrastructure.   What You’ll Do Drive technical sales & executive influence Partner with Account Executives to lead complex deals with large enterprises and digital native businesses and build trusted relationships with technical leaders (CTOs, Heads of AI/ML, Platform Leads) Evaluate customer architectural needs, uncover potential bottlenecks, and design end-to-end GPU cloud solutions Author comprehensive proposals & architecture diagrams and collaborate with teams on Bill of Materials (BOMs), and rack elevations for multi-node GPU clusters Lead hands-on proof-of-concept (PoC) activities & benchmarking for customers Design, execute, and deliver technical PoCs and custom prototypes to demonstrate Lambda’s performance, reliability, and value Run benchmark evaluations across training and inference workloads to show tangible performance and cost advantages over competitors Architect & optimize AI/ML workloads Guide enterprise engineering teams on structuring their AI lifecycle—from data ingestion and distributed training (SLURM, Kubernetes) to inference optimization (vLLM, TensorRT-LLM) and observability Provide architectural guidance on high-performance networking (InfiniBand, RoCE), distributed storage, and cluster topologies to ensure maximum GPU utilization Champion customer feedback & product advocacy Serve as the technical voice of the customer internally, funneling field insights, product gaps, and feature requests directly to Lambda’s Product and Engineering teams Create field enablement assets, technical whitepapers, architectural blueprints, and lead technical workshops for prospective clients & partners Represent Lambda as a subject matter expert at industry conferences, webinars, and technical community events Reinforce Lambda’s culture Contribute positively throughout the organization Maintain a high level of agility and responsiveness Hyper-focused on customer satisfaction You Have a proven track record deploying, benchmarking, and optimizing workloads on NVIDIA GPU architectures (e.g., HGX platforms, NVLink) using deep learning frameworks (PyTorch, NeMo) and inference engines (vLLM, TensorRT-LLM) Have 8+ years of experience designing, deploying, and scaling enterprise cloud infrastructure Have 4+ years in a Solution Architect, Solution Engineer, or technical customer-facing capacity supporting complex cloud environments Have 3+ years of hands-on experience architecting and deploying cloud-based AI/ML workloads Have strong experience with modern infrastructure orchestration tools such as Kubernetes, Docker, SLURM, Terraform, and Ansible Have deep knowledge of cloud networking concepts, including high-speed interconnects (InfiniBand, RoCE), distributed file systems (NFS, NVMe-oF, Weka, VAST), security, and cost optimization Have experience coding in Python, Go, C/C++ (CUDA) or similar programming language Have experience partnering with Account Executives to close complex cloud deals, present technical architectures to C-level stakeholders (CTOs, VP