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About the Role

We are 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.

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.

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.

Skills

GPU cloud
Capacity management
Provisioning
Workload execution
Reliability
Observability
Customer consumption
AI infrastructure
Cloud platforms
Developer experience
GPU compute
Infrastructure engineering
Operations
GPU availability
GPU utilization
Cluster provisioning
Networking
Storage
Scheduling
Orchestration
APIs
Workflows
Distributed systems
Kubernetes
Workload orchestration
Infrastructure reliability
Pricing
Packaging
Consumption models
Technical sales
Customer feedback
Competitive differentiation
GPU utilization metrics
Provisioning metrics
Workload reliability metrics
Infrastructure consumption metrics
Adoption metrics
Retention metrics
Product launch
Product adoption
Product iteration
Cloud infrastructure
Compute
Platform
Developer tooling
AI infrastructure products
Technical products
ML engineers
AI researchers
Technical users
Cloud infrastructure concepts
GPU infrastructure
AI training
AI experimentation
AI inference
Data analysis
Customer behavior analysis
Product judgment
Cloud infrastructure unit economics
Prioritization
Tradeoff analysis
Written communication
Verbal communication
Ambiguous environments
GPU provisioning
Cluster management
Distributed compute
Slurm
Ray
PyTorch
Distributed training
Reserved capacity
On-demand compute
Utilization optimization
Cloud consumption models
Data center operations
Hardware operations
Networking operations
Infrastructure operations teams

Location

New York City
San Francisco

Work Type

Hybrid

Experience Level

7+ years of product management experience
3+ years building cloud infrastructure, compute, platform, developer tooling, or AI infrastructure products

Education Level

BS in Computer Science, Engineering, or equivalent practical experience.

Salary/Compensations

$200,000—$250,000 USD

Benefits

Discretionary bonus
Meaningful equity
Comprehensive 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.

About the Company

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.
Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.
We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Equal Opportunity

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.