Solution Architect (AI)

TL;DR

Solution Architect (AI Cloud): Designing and optimizing high-performance GPU cloud solutions for AI researchers and enterprises with an accent on end-to-end architecture, benchmarking, and workload optimization. Focus on architecting distributed training and inference pipelines, managing high-speed interconnects, and delivering technical PoCs.

Location: Hybrid: Must be based in San Francisco, San Jose, or Bellevue (presence required 4 days per week in office).

Salary: $226,000 – $355,000 per year

Company

Lambda is a leader in AI cloud infrastructure, providing superintelligence compute power to thousands of customers, from AI researchers to hyperscalers.

What you will do

• Partner with Account Executives to lead complex enterprise deals and build relationships with technical leaders (CTOs, Heads of AI/ML).
• Evaluate customer needs and design end-to-end GPU cloud solutions, including architecture diagrams and Bill of Materials (BOMs).
• Lead hands-on proof-of-concept (PoC) activities and benchmark evaluations for training and inference workloads.
• Guide engineering teams on the AI lifecycle, focusing on distributed training (SLURM, Kubernetes) and inference optimization (vLLM, TensorRT-LLM).
• Provide architectural guidance on high-performance networking (InfiniBand, RoCE) and distributed storage to maximize GPU utilization.
• Serve as the technical voice of the customer internally to influence product roadmaps and engineering priorities.

Requirements

• 8+ years of experience designing, deploying, and scaling enterprise cloud infrastructure.
• 4+ years in a Solution Architect, Solution Engineer, or similar technical customer-facing role.
• Proven track record with NVIDIA GPU architectures (HGX, NVLink), deep learning frameworks (PyTorch), and inference engines (vLLM, TensorRT-LLM).
• Strong experience with Kubernetes, Docker, SLURM, Terraform, and Ansible.
• Deep knowledge of high-speed interconnects (InfiniBand, RoCE) and distributed file systems (NFS, NVMe-oF, Weka, VAST).
• Proficiency in Python, Go, or C++/CUDA.

Nice to have

• Experience with end-to-end LLM fine-tuning, 3D parallelism, and Megatron-LM.
• Prior experience leading GTM initiatives, product launches, or publishing technical benchmarks.
• Experience integrating RESTful APIs, gRPC, and service-oriented architectures.

Culture & Benefits

• Generous cash and equity compensation.
• Comprehensive health, dental, and vision coverage for employees and dependents.
• 401k plan with 2% company match for US employees.
• Flexible paid time off policy.
• Wellness and commuter stipends for select roles.