Senior Product Manager, AI Infrastructure
About The Position
We’re looking for a Product Manager, AI Infrastructure to own the product experience for Lightning AI’s GPU cloud, from capacity and provisioning through workload execution, reliability, observability, and customer consumption. This role sits at the intersection of AI infrastructure, cloud platforms, and developer experience. You’ll define how customers discover, provision, configure, and operate GPU compute, while partnering closely with infrastructure engineering and operations to make the platform more reliable, efficient, and scalable. The right candidate understands that infrastructure itself is the product. You should be comfortable reasoning about GPU availability and utilization, cluster provisioning, networking and storage, scheduling and orchestration, workload reliability, and the APIs and workflows that expose these systems to customers. You’ll work across Engineering, Infrastructure, Sales, customers, and the executive team to determine what we build, how infrastructure capabilities are exposed and packaged, and where Lightning AI can differentiate from hyperscalers and other GPU clouds. This is a high-ownership role. You’ll investigate infrastructure and customer problems directly, use data to understand reliability and utilization, make technical tradeoffs with engineers, and drive products from problem definition through launch, adoption, and iteration. You’ll join the Product team and report to our VP of Product.
Requirements
- 7+ years of product management experience, including 3+ years building cloud infrastructure, compute, platform, developer tooling, or AI infrastructure products.
- Experience building technical products for developers, infrastructure teams, ML engineers, AI researchers, or other technical users.
- Strong understanding of cloud infrastructure concepts including compute, networking, storage, provisioning, scheduling, and orchestration.
- Familiarity with GPU infrastructure and the requirements of large-scale AI training, experimentation, or inference workloads.
- Technical depth to work directly with engineers on APIs, distributed systems, Kubernetes, workload orchestration, observability, and infrastructure reliability.
- Experience using data to understand infrastructure utilization, capacity, reliability, performance, and customer behavior.
- Track record of owning technical products from problem definition through launch and adoption.
- Strong product judgment and ability to turn complex infrastructure capabilities into simple customer experiences.
- Experience with pricing, packaging, consumption-based products, or cloud infrastructure unit economics.
- Strong prioritization skills and comfort making tradeoffs across customer needs, reliability, infrastructure efficiency, and engineering investment.
- Strong written and verbal communication across technical, customer, and executive audiences.
- Comfortable moving quickly and operating in ambiguous environments.
- BS in Computer Science, Engineering, or equivalent practical experience.
Nice To Haves
- Experience at a GPU cloud, neocloud, hyperscaler, AI infrastructure company, or infrastructure developer-tools company.
- Experience building products involving GPU provisioning, cluster management, capacity management, workload scheduling, or distributed compute.
- Familiarity with GPUs, Kubernetes, Slurm, Ray, PyTorch, distributed training, or similar infrastructure technologies.
- Experience with reserved capacity, on-demand compute, utilization optimization, or other cloud consumption models.
- Experience building infrastructure products that support large-scale AI training and inference.
- Experience working closely with data center, hardware, networking, or infrastructure operations teams.
Responsibilities
- Own the product vision and roadmap for Lightning AI’s GPU cloud infrastructure.
- Define how customers discover, provision, configure, and consume GPU compute.
- Build product experiences around GPU capacity, clusters, scheduling, networking, storage, and workload execution.
- Partner closely with infrastructure and platform engineering to improve availability, reliability, utilization, and performance.
- Develop a deep understanding of customer workloads, from experimentation and training through inference, and translate those needs into infrastructure capabilities.
- Use infrastructure and product data to identify capacity constraints, reliability issues, performance bottlenecks, and opportunities to improve the customer experience.
- Define the APIs, interfaces, and developer workflows through which customers interact with infrastructure.
- Make product tradeoffs across customer experience, infrastructure efficiency, reliability, cost, and engineering complexity.
- Own pricing, packaging, and consumption models in partnership with Ops, Sales, and Finance.
- Partner with GTM on positioning, technical sales conversations, customer feedback, and competitive differentiation.
- Define and track metrics across GPU utilization, provisioning, workload reliability, infrastructure consumption, adoption, and retention.
- Take products from problem discovery through requirements, launch, adoption, and iteration.
Benefits
- Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents.
- Meaningful Equity: RSUs that give employees a stake in the company's long-term success.
- Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.).
- Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance.
- Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge.
- Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments.
- Professional Development: Annual learning and development allowance to support your professional growth.
- Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being.
- Sabbatical Program: Four weeks of paid sabbatical leave after four years of service.
- Flexible Work: Flexible schedules and a hybrid work model for our office-based teams.
- In-Office Meals: Complimentary meals at our office hubs.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
