Senior Solution Engineer

Who you are

• 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 of Eng), and drive customer alignment
• Have demonstrated impact at an organizational/multi-departmental level and are effective mentoring junior SEs or architects
• Thrive in dynamic settings and embrace radical ownership of initiatives and outcomes
• Direct experience with end-to-end LLM fine-tuning, algorithm selection, pipeline design, or distributed training setups (3D parallelism, Megatron-LM)
• Prior experience with product launches, leading GTM initiatives, or publishing technical whitepapers/benchmarks
• Experience integrating RESTful APIs, gRPC, and service-oriented cloud architectures

What the job involves

• 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
• 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
• 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
• 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
• 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
• Contribute positively throughout the organization
• Maintain a high level of agility and responsiveness
• Hyper-focused on customer satisfaction

Benefits

• Health, dental vision
• 401k match
• 5 sick days and 12 paid holidays
• Flexible PTO
• Paid parental, medical, and caregiver leave