Forward Deployed Engineer APAC
Runpod
| Company | Runpod |
| Category | Uncategorised |
| Location | Remote - APAC |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 1 Apr 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
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.
As part of the Revenue Team, you’ll work closely with customers, the sales team, the product team, the engineering team and the support team to ensure a seamless and delightful Runpod experience. Your role will focus on providing technical insights, resolving challenges, and building trust with customers. Our team is dedicated to delivering exceptional solutions and fostering collaboration across functions to make the platform as smooth and efficient as possible.
This Forward Deployed Engineer will support the growth of our cloud platform. This role ensures customers experience seamless operations, addressing technical challenges, guiding onboarding, and collaborating with engineering and sales teams. Ideal candidates combine technical expertise with strong communication skills to enhance customer satisfaction and improve our platform.
You’ll play a key role in solving technical challenges, shaping the customer experience, and driving product improvements. By building strong customer relationships and collaborating across teams, your contributions will directly enhance operational efficiency, customer satisfaction, and the success of Runpod.
Responsibilities:
- Participate in sales meetings with customers, explain Runpod’s specific technologies, provide architectural recommendations, and build proof-of-concept solutions to support onboarding for potential high-spending customers.
- Troubleshoot and resolve critical or complex technical issues escalated by customers, including those related to configuration, performance, functionality, compatibility, or code errors in Runpod’s products or services.
- Utilize various tools and methods, such as code analysis, scripting for testing, log analysis and remote access, to identify root causes and deliver solutions or workarounds.
- Communicate effectively with customers and internal teams, including engineering, sales, supply and product management teams, to ensure customer satisfaction and integrate valuable feedback.
- Assist the support team in troubleshooting and resolving escalated technical tickets, collaborate with the engineering team to provide workarounds or bug fixes, and work with the infrastructure team to address GPU server-related issues.
- Contribute to product development and testing efforts by relaying feedback from customers and the support team to the engineering team, helping to shape product improvements.
- Create and maintain technical documentation, such as knowledge base articles, FAQs, guides, and manuals, while also developing and delivering training sessions, webinars, and demos for customers, partners, and internal teams.
Requirements:
- Bachelor's degree in a relevant field (e.g., Computer Science, Computer Engineering, Software Engineering, Information Technology, or a related field) or equivalent professional experience.
- 3+ years of professional experience in software development.
- Strong problem-solving skills and ability to work in a collaborative environment.
- Familiarity with applied AI use cases such as inference, fine-tuning, LLM-based applications, or agentic systems.
- Excellent communication skills and attention to detail.
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