Technical Program Manager (Software Engineer)

Runpod

1d•$140,000 - $165,000•Remote

About The Position

Runpod is the AI Developer Cloud, used by over a million developers to experiment, train, fine-tune, deploy, and scale AI. The platform has processed more than 20 billion inference requests. We are at an inflection point for AI infrastructure and are building the platform for the next generation of developers. We are a small, remote-first team that values ownership, speed, and impact. We are looking for individuals who are passionate, driven by urgency, and want to make a significant impact. We are seeking a Technical Program Manager (TPM) with a strong understanding of distributed systems, including their construction and failure modes, combined with exceptional organizational and communication skills. The ideal candidate is a proactive self-starter who excels in a fast-paced, dynamic environment and can confidently navigate ambiguity to drive execution. As a TPM at Runpod, you will lead complex, cross-functional programs involving product and platform teams, collaborating closely with engineering leads and stakeholders across the company. Your work will be crucial in building the core of our cloud platform, specifically the systems responsible for scheduling, scaling, routing, and running customer workloads on GPU infrastructure across various regions. You will be responsible for early risk identification, keeping teams focused on priorities, and delivering high-impact work that provides tangible value to our customers. The ideal candidate is a dynamic problem solver, not just a process follower.

Requirements

3+ years in technical program management or software/infrastructure engineering, leading complex programs for cloud or infrastructure products.
Hands-on engineering experience on production distributed systems, with deep understanding of consistency and availability tradeoffs, queueing, scheduling, autoscaling, load balancing, failure handling, and performance at scale.
Hands-on familiarity with cloud infrastructure fundamentals: compute, networking, storage, containers and orchestration, and multi-region architectures.
Ability to read architecture docs, review designs, and hold credible technical conversations with senior engineers, including on reliability, latency, and capacity tradeoffs.
Experience with observability and operational practices (metrics, logging, tracing, SLOs, incident response) and using them to drive program decisions.
Proven track record of delivering multiple high-impact programs across 3+ cross-functional teams, from planning through launch.
Strong quantitative skills, with the ability to turn system and cost data into clear recommendations.
Deep understanding of the software development lifecycle and how engineering teams design, build, test, and ship production systems.
Exceptional written and verbal communication, with the ability to align stakeholders across teams and functions.
Ownership mindset: highly organized, proactive, and calm under pressure, favoring clarity and follow-through over rigid process.

Nice To Haves

Previous experience in AI/ML developer platforms or GPU/cloud infrastructure-focused organizations.
Experience in a fast-paced startup environment.
Technical degree in Computer Science, Engineering, or related field.

Responsibilities

Partner with engineering leads to understand squad architecture, constraints, and technical debt, and build plans that reflect how the systems actually behave.
Own planning and delivery for complex, multi-team programs: scope, sequencing, dependencies, and timelines, with close attention to cross-service and cross-region dependencies.
Identify technical risk early (scaling limits, failure modes, capacity constraints, migration complexity) and drive mitigation before it reaches customers or commitments.
Participate in design and architecture reviews, surfacing gaps in rollout plans, observability, and fault tolerance.
Drive launch readiness and safe rollout of platform changes, including staged releases, rollback plans, load and failure testing, and operational handoff.
Serve as the primary point of contact for stakeholders, with clear, regular status updates and risks escalated early alongside options and recommendations.
Work with Data, Product, and Engineering leads to define and track success metrics for performance, reliability, utilization, and cost, tied to customer outcomes.
Partner with SRE to build visibility into system health, and help leadership balance investment in reliability, scale, and new capabilities.
Coordinate with Supply and Data Center teams on how capacity and infrastructure changes affect platform roadmaps.
Run post-launch and post-incident reviews, and drive the resulting improvements to completion.