Engineering Manager - Cloud

Runpod is pioneering the future of AI and machine learning, offering cutting-edge cloud infrastructure for full-stack AI applications. Founded in 2022, we are a rapidly growing, well-funded company with a remote-first organization spread globally. Our mission is to create a foundational platform for developers to build and run custom AI systems that scale. Join us as we shape the future of AI.

We’re hiring an Engineering Manager to lead a high-impact product engineering team building customer-facing features across Runpod’s console, APIs, and developer workflows. You’ll take ownership of a roadmap area end-to-end - partnering with Product and Design to shape scope, then guiding your team through architecture, execution, quality, and launch.

This role is ideal for a leader who’s shipped at millions-of-users scale , thrives in fast-moving environments, and can go deep technically in Linux systems internals and/or cloud systems engineering - you have experience building cloud platforms (control planes, orchestration, networking, storage primitives, kubernetes components), not just applications running on top of them. You’ll help Runpod deliver the fastest, most intuitive path for builders to train and deploy AI in production.

Responsibilities:

Own Feature Delivery for a Product Area: Lead a team of engineers responsible for shipping new functionality and iterating existing product surfaces. Deliver predictable, high-velocity outcomes that improve customer experience and business value.

Plan and Execute Roadmaps: Translate product strategy into clear technical plans, milestones, and success metrics. Identify tradeoffs early and manage scope, risk, and timelines.

Technical Leadership & Architecture: Drive pragmatic system design for product-layer services and workflows, ensuring scalability, performance, and consistency with Runpod’s platform.

Build and Grow a Strong Team: Hire, mentor, and develop engineers; set expectations, provide feedback, and create a culture of ownership, speed, and craft in a remote-first environment.

Quality & Reliability for Product Surfaces: Improve automated testing, release safety, observability for customer-facing systems, and regression prevention. Ensure on-call health for your team’s services.

Cross-Functional Collaboration: Partner tightly with Product, Program management, Support, GTM, and Infrastructure counterparts. Coordinate dependencies cleanly while maintaining clear ownership.

Operational Excellence: Establish team rituals and delivery systems (sprints/kanban, retros, design reviews). Use data to improve cycle time, throughput, and feature adoption.

Customer-Driven Execution: Stay close to user needs by incorporating feedback, analytics, and support signals into prioritization and iteration.

Requirements:

Engineering Management Experience: 2+ years managing a team of high performance software engineers, including ownership of roadmap delivery, hiring/firing, performance, and team culture.

High-Scale Product Delivery: 6+ years as a software engineer building and shipping products used by millions of users , with clear evidence of personal impact.

Systems-Level Technical Depth: Strong experience with Linux systems internals and/or cloud systems engineering - ideally building platform capabilities (orchestration, control planes, distributed services, networking or storage layers).

Backend or Full-Stack Proficiency: Comfortable reviewing and contributing to code in modern stacks; Go, Python, and/or TypeScript experience preferred.

Distributed/Cloud-Native Architecture: Solid understanding of microservices, APIs, eventing, data stores, and service-to-service communication patterns.

Delivery & Metrics Mindset: Experience running execution processes and using metrics like cycle time, throughput, adoption, and escape defects to improve team flow.

Remote-First Leadership: Proven ability to communicate clearly, align stakeholders asynchronously, and sustain momentum across time zones.

Successful completion of a background check.

Preferred Qualifications:

Experience building AI/ML + developer platforms, workflow-heavy products, or infrastructure-adjacent product layers (e.g., job orchestration UX, deployment flows, usage/billing, observability surfaces).

Familiarity with Kubernetes-based platforms, container runtimes, scheduling concepts, or GPU/accelerator workflows.