Jobs at Runpod

Provide advanced L2 technical support for Runpod customers: troubleshoot escalated issues, analyze logs and code, use scripting and diagnostics, liaise with engineering and infra teams, create documentation and training, and deliver multi-channel support including weekend availability.

Own the technical lifecycle and operational health of a global high-density GPU fleet. Validate hardware, benchmark performance, monitor uptime and SLAs, automate operations using LLMs/agents, perform deep network and system-level troubleshooting, coordinate incident communications, and support infrastructure partners.

Lead and scale Forward Deployed Engineering and Technical Support teams, owning customer technical outcomes from pre-sales through deployment. Define engagement models, SLAs/SLOs, on-call/escalation structures, tooling, and feedback loops into Product and Engineering. Partner cross-functionally to prioritize roadmap, improve self-service, and drive operational discipline.

Drive full-cycle enterprise sales to acquire strategic AI/ML and infrastructure customers. Prospect, qualify, negotiate complex high-ARR deals, manage pipeline and forecasts, partner with engineering, and ensure smooth handoffs to customer success. Represent Runpod at customer meetings and industry events.

Lead strategy, roadmap, and business performance for a core AI infrastructure product area. Drive customer research, KPI-driven roadmaps, business cases, cross-functional launches, and measurable outcomes for adoption, retention, revenue, and platform expansion.

Lead strategic sourcing and high-value negotiations for cloud infrastructure procurement. Manage vendor relationships, act as legal liaison, perform financial and risk analysis, and align procurement strategy with engineering and finance. Drive cost optimization and complex contract structuring for large-scale cloud deployments.

Lead product marketing for Runpod's AI infrastructure platform: define positioning and messaging, run launches, own competitive intelligence and sales enablement, create technical long-form content, build AI-assisted content workflows, conduct customer research, and align GTM across product, marketing, and sales to drive awareness, adoption, and revenue.

Lead and execute marketing operations: build systems and workflows across HubSpot, Salesforce, Webflow, analytics and attribution; ensure clean campaign tracking, lead routing, PQL/MQL definitions, funnel and revenue reporting; run QA, documentation, and cross-functional rhythms with RevOps, Sales, Finance, Product, and Data to provide decision-ready marketing measurement.

Lead a small People team, partner with the COO and execs on people strategy and org design, build scalable people operations (HRIS, benefits, compliance), design compensation and performance systems, manage budget and vendor relationships, ensure legal compliance, and drive culture, engagement, and employee experience across a remote, global workforce.

Lead Revenue Operations, owning CRM architecture, data infrastructure, forecasting, reporting, compensation and territory design, and oversight of Deal Desk and Enablement. Drive GTM alignment, implement revenue technology and AI-powered automation, and support PLG and enterprise motions to scale ARR and operational efficiency.

Manage a portfolio of existing accounts to drive retention, renewals, upsells, and expansion. Monitor account health and usage, conduct business reviews, build account plans and forecasts, liaise with product/engineering/support, maintain CRM data, handle renewals and negotiations, and occasionally travel to customers or industry events.

Design, build, and maintain cloud infrastructure software (primarily in Go) to manage VMs across global data centers. Collaborate on product requirements, participate in code reviews, optimize performance and reliability, contribute to architecture decisions, and stay current with industry trends.

Lead and grow a distributed datacenter storage engineering team owning end-to-end storage from NAND/NVMe to filesystems. Design and operate SAN, NFS, and parallel filesystems (VAST, Lustre), optimize performance (RDMA, GDS), ensure reliability, automation, observability, and collaborate with networking, GPU platform, SRE, and product teams.

Build and maintain frontend and backend platform components using Python and TypeScript, support the open-source SDK, collaborate with engineering and AI teams, write tests and CI-friendly code, fix bugs, and participate in code reviews and mentorship.

Design and implement multitenant workload and network isolation for bare-metal and virtualized GPU infrastructure. Harden Linux kernel and container runtimes, perform threat modeling and penetration testing, write low-level security code (C/Go/Rust), mitigate GPU and PCIe security risks, and lead incident response and forensic work for ephemeral container environments.

Secure customer-facing products, APIs, and internal services through threat modeling, architecture and code reviews. Remediate vulnerabilities by coding fixes in Python/Go/JS/TS. Build and manage SAST/DAST/SCA security pipelines in CI/CD. Configure WAFs, API gateways, and bot protection. Provide secure coding guidance, run bug bounty triage, and support compliance (SOC 2, ISO 27001, GDPR).

Ensure stability and resilience of Runpod's distributed AI platform by defining SLIs/SLOs, leading incident response, building observability and reliability tooling, automating operational workflows, and partnering with engineering teams to reduce toil and improve production readiness.

Lead and scale core cloud and bare-metal infrastructure including SRE, global and HPC networking, and distributed storage. Define SLOs/SLAs, incident response, observability, and IaC. Architect InfiniBand/RoCE networks and high-performance storage to support large GPU workloads. Hire and mentor managers and senior ICs, partner with product and program teams to forecast capacity and drive reliability, throughput, and low-latency infrastructure at scale.

Own end-to-end product design for Runpod's AI infrastructure platform, turning complex workflows (compute, deployment, storage, networking, billing, observability, model ops) into intuitive, polished experiences. Rapidly identify UX problems, prototype high-fidelity designs, define design systems, partner with Engineering and Product, and use user research and analytics to iterate and raise product craft and developer trust.

Lead a product engineering team to own roadmaps, design scalable cloud-native systems, ship customer-facing features, ensure quality and reliability, hire and mentor engineers, and coordinate cross-functional delivery.