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Engineering Manager - Product & Platform Delivery

175k – 250kUnited StatesRemote
Summary

Leads engineering team building customer-facing features for AI/ML cloud platform's console, APIs, and workflows. Requires 2+ years management experience, 6+ years high-scale engineering, and deep expertise in Linux/cloud systems.

About the role

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.
  • Track record of scaling teams in high-growth environments while keeping quality high.
  • Open-source contributions in cloud-native, systems, or ML-adjacent projects.

Compensation

  • Competitive base pay: $175,000 - $250,000 (may vary based on experience, qualifications, and location).
  • Meaningful equity via stock options.
  • Generous medical, dental & vision plans (100% coverage for employees).
  • Flexible PTO.
  • $1,200 Home Office & Equipment Stipend.
Skills
GoPythonTypeScriptKubernetesLinuxmicroservicesAPIscloud systemsdistributed systemsorchestration
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