Jobs at Lambda

Lead hands-on hardware NPI and integration for Lambda's HPC platform: bring up OEM and white-label AI/ML, compute, storage, and networking systems; debug and resolve hardware issues; drive cross-functional production readiness, vendor engagement, BOM review, and fleet reliability at scale.

Lead design and implementation of high-performance distributed storage systems and protocols (object, block, file) for AI infrastructure. Set technical direction, author designs, mentor engineers, integrate with hardware (NVMe, DPUs, GPU-direct), optimize performance, build benchmarking and observability tooling, and drive cross-team deployments and incident response in multi-petabyte data center environments.

Design, deploy, and operate Kubernetes clusters across AWS and bare-metal datacenters. Build automation for provisioning, upgrades, and scaling. Own reliability, performance, and security of production workloads. Implement observability, logging, and alerting. Partner on cloud-native services and CI/CD; lead incident response and post-mortems; set platform standards and mentor engineers.

Operate and scale bare-metal Kubernetes clusters to thousands of nodes, manage incidents and on-call rotation, support customers, collaborate with HPC/datacenter teams, build automation and tooling in Go/Python, create control-plane services/operators, automate cluster lifecycle, and define SLOs/SLIs for platform reliability.

Lead design and implementation of a highly available GPU/CPU host and instance lifecycle control plane. Bridge firmware, kernel, DPU, and semiconductor architecture with distributed systems. Provide technical leadership, mentor senior engineers, set engineering standards, collaborate with product and data-center teams, and translate customer requirements into scalable infrastructure.

Lead Public Cloud FP&A: own consumption-based revenue forecasting, OpEx and headcount planning, GTM finance partnership, segment and pricing analysis, internal allocation, and executive reporting to drive revenue, margin, and capital efficiency.

Build and maintain scalable Kubernetes control-plane services, operators, and automation for GPU-aware orchestration. Partner on networking (CNI, InfiniBand/RDMA/GPUDirect), observability, inference platform services, tooling/CLIs, and on-call production support for large-scale AI clusters.

Lead design and implementation of scalable supply chain, procurement, inventory, asset management, and financial workflows. Translate business requirements into system solutions (NetSuite, Coupa, PLM), drive testing, deployment, training, governance, master data initiatives, and continuous improvement across cross-functional stakeholders.

Design, develop, and maintain high-performance distributed storage software and protocols (file, block, object). Integrate with hardware (NVMe, DPUs, GPU-direct), optimize performance and scalability, troubleshoot production data centers, collaborate with networking, compute, control plane and observability teams, and lead/mentor engineering teams.

Design and implement a vendor-agnostic storage control plane for high-performance AI clusters. Build Kubernetes CRD-based orchestration, reconciliation loops, multi-tenant isolation, capacity and placement engines, and observability for petabyte-scale storage across diverse vendors and protocols.

Draft, review, and negotiate high-value commercial agreements (customer, data center, partner/reseller, distributor, marketing). Lead enterprise deal negotiations, advise cross-functionally on contract structure and risk, use legal technology to streamline contracting, and improve templates and playbooks while providing practical business-focused legal guidance.

Lead technical accounting research and memos for complex U.S. GAAP transactions; analyze accounting impacts for revenue, equity, debt, business combinations, leases, and stock-based compensation; support IPO readiness, S-1/10-K preparation, consolidated financial statements, audits, SOX readiness, and cross-functional guidance. Contribute to M&A, system implementations, and controls/process improvements.

Own and drive observability product strategy for Lambda Cloud: define telemetry signals, build diagnostics to distinguish customer vs platform issues, partner with SRE/fleet/console/API teams, define SLIs/SLOs/SLAs, engage customers, and measure adoption to iterate and launch observability features across GPU clusters.

Own the billing and metering product for a large GPU cloud: define per-minute metering, ensure billing accuracy and reconciliation, manage credits and invoicing lifecycle, enable pricing and contract launches, expose billing via public APIs, productize commerce-related areas like fraud and bad-debt, and instrument and iterate on customer billing experiences.

Lead and grow the Platform product group (Security, Observability, Billing) as a player-coach. Own platform product strategy and roadmap, hire and manage PMs, partner with platform engineering, deliver horizontal capabilities for Lambda's AI cloud (billing, identity, telemetry), make data-driven decisions, and ensure enterprise-grade trust and accurate usage-based billing.

Own the GPU hardware product roadmap and fleet lifecycle. Lead NVIDIA platform introductions, define node and cluster configurations, align partner roadmaps, translate customer demand and benchmarks into investment recommendations, and partner with data center, supply chain, and engineering teams to launch, measure, and iterate on hardware offerings.

Own and improve reliability, performance, and capacity of Lambda's production storage fleet. Build monitoring, alerting, CI/CD, and self-healing automation; troubleshoot storage incidents and low-level I/O/network issues; automate deployments and incident workflows; participate in on-call to reduce MTTR.

Lead development and enforcement of Physical Infrastructure Cabling Standards across global data centers; author BoDs, SOPs, and MOPs; manage vendors and BOMs; support NPI and deployments; perform site assessments, QC/QA, and drive process improvements to optimize connectivity for GPU cluster deployments.

Lead financial modeling, valuation, due diligence, and execution for M&A, strategic investments, and capital raises. Drive market and capital markets analysis, develop investment theses and financing strategies, build executive materials, and cultivate strategic partnerships to support company growth.

Support identification, evaluation, and execution of M&A, strategic investments, and partnerships for data center and digital infrastructure assets. Lead financial modeling, valuation, due diligence, and prepare business-case memos and executive presentations. Collaborate cross-functionally with infrastructure, site selection, finance, and legal teams; track industry trends and develop investment theses and market analyses.