Product Manager (AI Cloud Console)

Location: Hybrid, with presence in the Bellevue or San Francisco office 4 days per week; Tuesday is the designated work-from-home day.

Annual salary: Bellevue $338,000–$450,000; San Francisco $375,000–$500,000.

Company

Lambda is an AI cloud infrastructure company providing GPU compute and related cloud services to AI researchers, enterprises, and hyperscalers.

What you will do

• Own the console as a unified product across GPU instances, reserved capacity, clusters, bare metal, storage, networking, Managed Kubernetes, billing, and support.
• Define navigation, identity, permissions, resource naming, states, errors, empty screens, and other cross-product interaction standards.
• Ensure the console, API, command line, and infrastructure-as-code interfaces represent the same resources, names, and rules.
• Improve the customer journey from signup to first workload while supporting operators and platform teams with bulk actions, filtering, deep links, quotas, spend visibility, and access control.
• Partner with service product managers, design, front-end engineering, and other teams to coordinate launches and establish review standards.
• Define success metrics, analyze customer and support data, and iterate based on completion rates, time to first result, and support load.

Requirements

• 10+ years of product management experience, including ownership of a customer-facing console, dashboard, or developer surface for a cloud, infrastructure, or developer platform.
• Experience establishing interaction patterns, design systems, or surface standards adopted by teams outside the direct reporting line.
• Experience consolidating separately built product surfaces into a coherent product while making clear prioritization and scope decisions.
• Strong understanding of cloud infrastructure concepts including identity, permissions, quotas, regions, capacity, telemetry, billing, organizations, teams, projects, roles, and API keys.
• Ability to use research and instrumentation to resolve product disagreements and turn ambiguous customer, technical, and commercial inputs into precise product definitions.
• Clear written and verbal communication, sound judgment, and the ability to make decisions across multiple teams.

Nice to have

• Experience with machine learning or data platform surfaces such as notebooks, training jobs, model endpoints, or experiment tracking.
• Experience improving signup-to-first-paid-usage conversion and activation.
• Experience partnering with a front-end platform team on component libraries, design tokens, or shared application shells.
• Experience owning documentation, in-product guidance, accessibility, or interfaces serving both human users and automated callers.

Culture & Benefits

• Collaborative work across product, engineering, design, and service teams without functional silos.
• Cash and equity compensation.
• Health, dental, and vision coverage for employees and dependents.
• Wellness and commuter stipends for select roles.
• 401(k) plan with a 2% company match for USA employees.
• Flexible paid time off.