Director of Software Engineering - Product & Platform Delivery

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 looking for a Director of Software Engineering to lead and scale Runpod’s product-delivery engineering organization. This role owns the end-to-end delivery of customer-facing platform features - from roadmap execution to high-quality launches - across multiple teams. You’ll build the operating rhythm, culture, and technical direction that help Runpod ship quickly, safely, and consistently as demand scales.

You will partner tightly with Product, Design, GTM, and Infrastructure leadership.Your focus is ensuring our customers experience Runpod as the fastest, most intuitive path to training and running AI inference workloads.

Responsibilities

• Own Product Feature Delivery: Lead multiple engineering teams responsible for shipping new features and improving Runpod’s customer experience across console, APIs, and developer workflows. Ensure predictable, high-velocity execution.
• Translate Roadmap into Results: Partner with Program management, Product and GTM to shape strategy, define quarterly goals, and convert requirements into clear technical scopes, milestones, and measurable outcomes.
• Build a High-Output Org: Hire, mentor, and grow engineering managers and senior ICs. Create a culture of ownership, speed, and craft in a remote-first environment.
• Drive Cross-Functional Launch Excellence: Run feature lifecycle processes - discovery support, design/architecture reviews, build phases, QA and rollout plans, release comms, and post-launch iteration.
• Improve Engineering System & Flow: Establish and evolve standards for lifecycle management, sprint/kanban execution, code review, CI/CD quality gates, release safety, documentation, and retrospectives.
• Customer-Backed Prioritization: Ensure engineering work aligns to user impact and business value. Constantly leverage customer insights, product analytics, and operational data to refine priorities.
• Quality & Velocity Leadership: Balance speed and reliability by improving automated testing, staging/preview environments, observability for product surfaces, and regression prevention.
• Technical Guidance on Product Surfaces: Provide architectural oversight for product systems (backend services, APIs, user workflows, integrations), ensuring scalability and coherence without bottlenecking teams.
• Partner with Infrastructure Leadership: Coordinate dependencies cleanly with infra/SRE teams to ensure high quality product delivery.

Requirements

• Engineering Leadership Experience: 7+ years leading software engineering teams including managers and/or multiple squads, with a proven record of shipping customer-facing products.
• Product Delivery Strength: Demonstrated ability to take complex roadmap goals from concept through launch, balancing scope, risk, timelines, and quality.
• Full-Stack or Backend Product Expertise: 8+ years building SaaS, platforms, or developer-facing products. Comfortable with modern backend stacks and pragmatic architectural decisions.
• Technical Fluency: Ability to go deep in system design and code when needed; experience with Go, Python, and/or TypeScript strongly preferred.
• Remote-First Operating Excellence: Experience building culture, accountability, and momentum across distributed teams.
• Process & Metrics Mindset: Strong use of delivery metrics (cycle time, throughput, escape defects, reliability, adoption), and experience improving team flow.
• Communication & Collaboration: Clear written and verbal communication, strong stakeholder management, and calm leadership through ambiguity.
• Successful completion of a background check.
  

Preferred Qualifications

• Experience building cloud or developer platforms, APIs, or workflow-heavy products used by technical customers.
• Expertise with AI/ML product surfaces such as job orchestration UX, model deployment flows, observability dashboards, or billing/usage systems.
• Track record of scaling product teams in high-growth environments.
• Open-source contributions or recognition with communities o