[Remote] Super Intelligence Support Account Lead at Lambda

United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

5+ years in Support Account Management, Technical Account Management, or Support Engineering within cloud, enterprise IT, or infrastructure environments
Proven experience in HPC environments, showcasing expertise in Linux cluster administration, with strong preference for Kubernetes and/or Slurm for cluster orchestration
Proven ability to own escalations end-to-end, with strong skills in incident management and structured communication
Solid understanding of cloud and HPC infrastructure (GPU cloud, Kubernetes, Linux clusters, or public cloud platforms)
Skilled at analyzing ticket trends, incident timelines, and support metrics, turning them into actionable improvements
Strong relationship management skills with both technical and executive-level stakeholders
Comfortable leading cross-functional collaboration, ensuring engineering and operations stay aligned on customer priorities
Experience mentoring or guiding support engineers through escalations or complex cases

Responsibilities

Serve as the primary support contact for assigned Super Intelligence accounts, ensuring consistent, high-quality customer experiences
Own the overall support health of assigned accounts, proactively monitoring for risks, recurring issues, and opportunities to improve reliability
Drive resolution for escalated issues by coordinating with Support, Data Center Ops, and Engineering teams—ensuring timely communication and accountability
Lead operational reviews (QBRs/MBRs), presenting ticket trends, SLA adherence, incident summaries, and improvement actions
Develop and maintain account-level success and support plans aligned to customer priorities and workloads
Document solutions, escalations, and RCA outcomes to build scalable runbooks and strengthen internal processes
Partner with Product and Engineering teams to ensure customer pain points are visible, tracked, and resolved
Contribute to Lambda’s support operations playbooks, refining how we handle incidents, escalations, and enterprise account management
Curate and document custom scripts, solutions, or customer-requested customizations outside of Lambda’s reference architecture when required
Participate in an on-call schedule

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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