GTM Manager - Public Cloud Utilization Strategy at Lambda

San Francisco, California, United States

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Not SpecifiedCompensation

N/AExperience Level

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Requirements

7+ years of experience in GTM strategy, business operations, or cross-functional leadership roles within public cloud, SaaS, or infrastructure organizations
Strong ability to influence senior executives and communicate actionable insights in board-level and C-suite settings
Proven track record of developing strategies, securing buy-in, and leading execution with measurable outcomes
Strong financial and analytical acumen, with the ability to link utilization metrics directly to growth, margin, and profitability
Cross-functional leadership experience, collaborating effectively with GTM, Product, Engineering, and Finance teams
Comfortable driving complex, high-impact programs across multiple stakeholder groups
(Preferred) Hold an MBA or equivalent experience in cloud business strategy and operations
(Plus) Bring product or program management experience in a cloud infrastructure context

Responsibilities

Develop and own the end-to-end strategy for public cloud utilization, driving maximum ROI, revenue efficiency, and gross margin improvement
Lead execution of utilization initiatives by aligning cross-functional stakeholders across GTM, Product, Engineering, Marketing, Partnerships, and FP&A
Diagnose and address root causes of underutilization through targeted solutions - including pricing strategies, GTM motions, sales plays, partnerships, or product enhancements
Translate utilization strategies into actionable GTM plays and customer engagement plans to accelerate adoption and optimize cloud usage
Partner with senior leadership to prioritize initiatives, secure alignment, and ensure measurable business outcomes
Serve as the primary owner and voice of public cloud utilization strategy in executive forums, shaping business direction with data-driven insights
Prepare and deliver executive-level briefings on utilization performance, pipeline alignment, and financial impact
Collaborate with C-level leadership to ensure cloud utilization strategy aligns with company growth and operational goals
Build and maintain dashboards and reporting to provide visibility into public cloud utilization, availability, and revenue impact
Partner with capacity planning, cloud operations, and FP&A to analyze revenue, cost structures, margin opportunities, and forecast accuracy

Skills

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

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