Top Tech Jobs & Startup Jobs

Build and operate internal support tooling for case triage, intelligent routing, diagnostics, incident workflows, and expert engagement. Develop AI-assisted automation, self-service diagnostics, observability dashboards, alerts, APIs, and Kubernetes-native controllers to improve reliability and reduce resolution time. Partner with Support/CX, Product, SRE, and engineering teams to prioritize initiatives, drive adoption, measure impact, and participate in on-call support.

Leads community engagement and partnership strategies across multiple markets, advising senior leaders on local risks, stakeholder sentiment, permitting, and development priorities. Builds relationships with officials, nonprofits, unions, businesses, and community organizations; negotiates community benefit and development agreements; oversees partnerships, investments, budgets, and engagement KPIs. Coordinates cross-functional teams across government affairs, communications, legal, development, operations, and people functions to support site selection, construction, permitting, and ongoing operations.

Provide legal counsel to CoreWeave’s U.S. West sales organization on complex cloud, SaaS, IaaS, PaaS, software licensing, partnership, and data processing transactions. Draft and negotiate commercial technology agreements, advise stakeholders on legal and commercial risks, support enterprise sales cycles, manage concurrent transactions, and improve contract templates, playbooks, policies, and processes. Coordinate with outside counsel and counsel senior business leaders on high-value and cross-border deals.

Lead CoreWeave’s product regulatory governance program and advise Product, Engineering, AI, Security, Supply Chain, and Operations teams. Responsibilities include reviewing products and AI capabilities, assessing international regulatory risks, embedding privacy, responsible AI, security, and data-governance requirements, advising on market entry and launches, monitoring global laws, and leading regulatory inquiries, audits, investigations, and remediation.

Debug and fix complex kernel and container runtime interactions for a large GPU fleet: investigate kernel crashes, cgroup and namespace edge cases, and scheduler/memory issues; develop and upstream kernel or container-runtime patches; build observability tooling and partner with hardware, platform, and fleet teams during incident response.

Own CoreWeave’s AI training infrastructure narrative, positioning, competitive messaging, customer evidence strategy, go-to-market approach, and sales enablement. Translate Kubernetes, scheduling, bare-metal performance, and distributed training capabilities into compelling messaging for AI research leaders, platform engineers, developers, and technical architects. Partner with technical teams on benchmarking, collaborate with Sales, Solutions Architects, and DevRel, and measure impact through deal velocity, contract value, competitive win rates, adoption, and retention.

Lead global supplier management for CoreWeave's AI infrastructure, overseeing technical sourcing and supplier materials management. Set supplier strategy, negotiate multi-year agreements, manage CTB and capacity, and resolve delivery or quality disputes. Partner cross-functionally and present supply risk and strategy to senior leadership to ensure build readiness and supply assurance for critical hardware components.

Lead and manage an SDR team to drive outbound prospecting and inbound lead qualification. Recruit, onboard, and coach SDRs, develop training and prospecting resources, collaborate with Sales and Marketing to generate pipeline, track performance metrics, and continuously improve processes while building career paths and a high-performance team culture.

Lead and coach a team of SDRs to drive outbound prospecting and manage inbound leads. Recruit, train, and ramp new reps, track performance metrics, collaborate with Sales and Marketing on pipeline strategies, and continuously refine SDR processes to scale outreach and career development.

Lead and grow the engineering team productizing and operating an inference offering. Drive roadmap execution with Product, improve reliability, observability, release and incident processes, integrate platform capabilities, and deliver developer-friendly tooling and application-layer enhancements to scale production ML workloads.