Jobs at Runpod

Define and execute the product vision and roadmap for Runpod’s AI cloud platform, including GPU infrastructure, serverless endpoints, APIs, foundational services, and developer experience. Lead and scale the product and design organization, engage customers, partner with engineering and infrastructure leadership, establish pricing and packaging, guide go-to-market strategy, and prioritize initiatives using product analytics and customer insights.

Lead Runpod’s Americas sales organization and revenue number across new business, expansion, and renewals. Manage and coach Account Executives and Account Managers, oversee forecasting and pipeline, lead complex enterprise deals and contract negotiations, build regional go-to-market strategy and sales playbooks, and convert product-led demand into revenue. Partner with Marketing, Product, Legal, and Finance while improving sales efficiency through AI and developing a remote-first team.

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.

Lead Runpod’s outsourced BDR program end to end, including vendor governance, staffing, enablement, coaching, quality assurance, funnel handoffs, forecasting, reporting, experimentation, and CRM integrity. Build scalable outbound strategies targeting technical buyers, manage performance against pipeline and conversion outcomes, and translate market feedback into improvements for Sales, Marketing, Product, and Partnerships.

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.

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.

Own the technical lifecycle and operational health of Runpod’s global high-density GPU fleet. Responsibilities include hardware validation and benchmarking, fleet monitoring, SLA and downtime auditing, network and systems troubleshooting, incident coordination, partner technical support, AI-assisted operational automation, and infrastructure tooling. The role requires Linux, Docker, NVIDIA GPU, datacenter networking, and performance-tuning expertise, with potential future on-call participation.

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 cross-functional programs ensuring GPU capacity meets demand. Partner with data center, host partners, engineering, and product to plan capacity, resolve vendor issues, translate utilization data into tradeoffs, build project plans, surface risks, and run post-mortems to improve supply, cost, and reliability.

Design and implement scalable data pipelines and a SOC2-compliant data warehouse. Support analytics and ML teams, enable real-time and batch ETL, mentor data engineers, and collaborate cross-functionally to drive data-driven decisions.

Lead developer-facing content, demos, tooling, and community programs to drive awareness, sign-ups, and activation for Runpod. Build integrations, speak at conferences, create technical content (blogs, videos, webinars), and feed product insights back to engineering. Own program strategy and measure impact of tools and outreach.

Build developer tooling, demos, and integrations for Runpod; produce technical content and run scalable programs (content, events, community); attend and speak at developer/AI conferences; surface product feedback and ship solutions autonomously to improve developer onboarding and platform adoption.

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.

Build and maintain frontend and backend components for an AI infrastructure platform using Python and TypeScript. Contribute to SDK development, collaborate with engineering and AI teams, write tests and maintain code quality, participate in code reviews, and support developer-focused tooling and integrations.

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.

Customer-facing technical engineer supporting sales and onboarding for Runpod's AI cloud. Troubleshoot escalated issues, build POCs, collaborate with engineering and product, create documentation, and train customers to ensure smooth deployment and operation of AI workloads.