Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform. The platform has processed more than 20 billion inference requests. We closed a $100M Series A in June 2026. We're at an inflection point for AI infrastructure, and we're building the platform the next generation of developers will depend on. Learn more in our CEO's funding announcement: https://www.runpod.io/blog/one-million-developers.
We're a small, remote-first team. We take ownership seriously, move fast, and ship work that more than a million developers rely on every day. We're looking for people who care deeply, build with urgency, and want to matter at scale.
The Director of Forward Deployed Engineering (FDE) & Technical Support leads two of Runpod's most customer-critical functions. The FDE team sits at the intersection of Solutions Engineering and Forward Deployed Engineering, serving as trusted technical advisors who assess customer environments, architect solutions, and own technical outcomes from pre-sales through deployment. They work hands-on where needed, but their primary role is solution ownership and conduit to Product and Engineering. The Technical Support team delivers fast, expert help across all customer tiers, from self-serve developers to strategic enterprise accounts. This role reports to the COO.
Responsibilities:Lead and scale both the FDE and Technical Support teams, defining engagement models, operating standards, headcount plans, and career development frameworks for each function
Own the FDE engagement lifecycle: technical discovery, environment assessment, solution architecture, PoC validation, and deployment guidance. Engage Sales at the right moments and ensure FDE coverage goes to the customers where it drives the most value
Set the standard for how FDEs operate: trusted advisors first, hands-on contributors where the situation calls for it, working through and alongside Product Engineering rather than as an independent delivery team
Own the field feedback loop by synthesizing patterns from FDE engagements and support escalations into clear, prioritized product input that directly shapes Runpod's roadmap
Run Technical Support across all tiers (Tier 1–3) with defined SLA/SLO frameworks, CSAT and TTR targets, escalation paths, and a developer-first knowledge base that scales self-service and reduces inbound volume
Drive operational discipline across the stack: Zendesk for support operations, HubSpot for customer health, Linear for engineering escalations, and Notion for internal knowledge and FDE documentation
Partner with Sales, Account Management, Product, and Engineering on pre-sales strategy, QBRs, escalations, and roadmap alignment. This role is a cross-functional connector, not a siloed function
10+ years in technical customer-facing roles: solutions engineering, field engineering, or a hybrid FDE function, with at least 4 years leading a team in a high-growth cloud infrastructure, SaaS, or AI/ML company
Deep technical fluency in GPU compute and AI/ML infrastructure; hands-on coding ability (Python, Docker/Kubernetes) is expected. This leader should be able to do the work, not just manage it
Demonstrated experience building or leading a technical engagement function that spans pre- and post-sales, with clear ownership of solution architecture and customer technical outcomes
Proven ability to build and run tiered support organizations: SLA/SLO frameworks, on-call structures, escalation paths, and the tooling and process to operate them at scale
Strong systems-builder instinct, comfortable creating structure where little exists: playbooks, triage frameworks, onboarding programs, and knowledge base architecture
Proficiency with Zendesk, HubSpot, Linear, and Notion; comfort using AI tools (Claude, Gemini, GPT) to accelerate documentation and triage at scale
Exceptional communicator across audiences. Equally at home in a technical architecture discussion with a customer's ML team and translating field observations into product priorities for Engineering leadership
Successful completion of a background check
The competitive base pay for this position ranges from 200,000 - $300,000 usd. This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location
Meaningful equity in a fast-growing company- everyone on the team receives stock options — your impact drives our growth, and you share in the upside.
Generous medical, dental & vision plans — we cover 100% for all employees and partial for dependents.
Flexible PTO- take the time you need to recharge
Most roles are remote work first with an inclusive, collaborative teams utilizing slack as the main form of internal communication
Join a passionate team on the cutting edge of AI infrastructure — where culture, learning, and ownership are at the heart of how we scale.
$1,200 Home Office & Equipment Stipend- We set you up for success from day one with gear and support to create your ideal workspace
Skills Required
- 10+ years in technical customer-facing roles (solutions engineering, field engineering, or hybrid FDE)
- At least 4 years leading a team in a high-growth cloud infrastructure, SaaS, or AI/ML company
- Deep technical fluency in GPU compute and AI/ML infrastructure
- Hands-on coding ability (Python)
- Hands-on experience with Docker and Kubernetes
- Demonstrated experience building or leading a technical engagement function spanning pre- and post-sales with ownership of solution architecture and customer outcomes
- Proven ability to build and run tiered support organizations (SLA/SLO frameworks, on-call, escalation paths)
- Proficiency with Zendesk, HubSpot, Linear, and Notion
- Comfort using AI tools (e.g., Claude, Gemini, GPT) to accelerate documentation and triage
- Strong systems-builder instinct: playbooks, triage frameworks, onboarding programs, knowledge base architecture
- Exceptional communication across technical and non-technical audiences
- Successful completion of a background check
Runpod Compensation & Benefits Highlights
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Healthcare Strength — Public listings indicate fully paid health benefits for full‑time employees, plus dental and vision coverage. Feedback suggests wellness programs also support overall health.
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Retirement Support — Public materials call out 401(k) matching as part of the package. Feedback suggests this provides structured long‑term savings alongside salary.
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Equity Value & Accessibility — Job postings state everyone on the team receives stock options. Feedback suggests this makes ownership broadly accessible across roles.
Runpod Insights
What We Do
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 empower innovators and enterprises to unlock AI's true potential, driving technology and transforming industries. Join us as we shape the future of AI. We are building Cloud services focused on accelerating AI adoption. Whether you're an experienced ML developer training a large language model, or an enthusiast tinkering with stable diffusion, we strive to make GPU compute as seamless and affordable as possible.
Why Work With Us
Our Guiding Virtues Give a sh*t - We want to work with people who care - about our customers and about each other. Look in the mirror - We deeply reflect on our own actions and seek to better ourselves. Courage over comfort - We tackle hard truths and tough situations directly, even when it makes us uncomfortable.
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Runpod Offices
Remote Workspace
Employees work remotely.
We’re remote-first, offering flexibility with virtual tools for collaboration. For those nearby, we have coworking spaces in SF and Seattle. Enjoy the choice of office or remote work, with a focus on flexibility and work-life balance






