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 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
Nice to Have
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
Salary Range Information
The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
About Lambda
Founded in 2012, with 500+ employees, and growing fast
Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
Our values are publicly available: https://lambda.ai/careers
We offer generous cash & equity compensation
Health, dental, and vision coverage for you and your dependents
Wellness and commuter stipends for select roles
401k Plan with 2% company match (USA employees)
Flexible paid time off plan that we all actually use
Equal Opportunity Employer
Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Skills Required
- On-site presence in San Francisco, San Jose, or Bellevue office 4 days per week
- 8+ years designing, deploying, and scaling enterprise cloud infrastructure
- 4+ years in a Solution Architect, Solution Engineer, or technical customer-facing role supporting complex cloud environments
- 3+ years hands-on architecting and deploying cloud-based AI/ML workloads
- Proven experience deploying, benchmarking, and optimizing workloads on NVIDIA GPU architectures (e.g., HGX platforms, NVLink)
- Experience with deep learning frameworks and inference engines (PyTorch, NeMo, vLLM, TensorRT-LLM)
- Strong experience with Kubernetes, Docker, SLURM, Terraform, and Ansible
- Deep knowledge of cloud networking and high-speed interconnects (InfiniBand, RoCE) and distributed file systems (NFS, NVMe-oF, Weka, VAST)
- Experience coding in Python, Go, C/C++ (CUDA) or similar languages
- Experience partnering with Account Executives to close complex cloud deals and present architectures to C-level stakeholders
- Demonstrated impact at an organizational/multi-departmental level and mentoring junior SEs or architects
- 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 and gRPC
Lambda Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lambda and has not been reviewed or approved by Lambda.
-
Fair & Transparent Compensation — Pay is considered competitive for an AI infrastructure company, with posted ranges and observed offers indicating strong packages for senior technical roles. Compensation is often characterized as competitive or top‑shelf, aligning with market expectations.
-
Healthcare Strength — Health, dental, and vision coverage are characterized as strong, with broad‑network plans noted and positive experiences highlighted. This foundation supports overall satisfaction with core insurance benefits.
-
Leave & Time Off Breadth — Flexible or unlimited PTO is described as actually used, complemented by paid holidays and sick time. Generous parental leave examples further expand the time‑off offering.
Lambda Insights
What We Do
Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.
