Developer Relations Engineer

About the role

You will own the technical narrative of RunPod by building and shipping developer tools that make the platform feel native to Python, JavaScript, and Go workflows. You will act as customer zero, validating every feature you ship by running real workloads on RunPod and turning your own friction into public documentation and demos. This role sits at the intersection of engineering, product, and marketing, requiring you to be technically credible enough to earn trust, close enough to product to influence roadmap decisions, and public enough to scale our message. You will design durable programs for content, community, and events that compound over time rather than relying on one-off wins. Every integration you build, every talk you deliver, and every tutorial you publish will directly accelerate onboarding, reduce friction, and increase platform retention. You will have the autonomy to identify gaps, prioritize integrations, and ship solutions independently without waiting for approval. The work is hands-on, urgent, and grounded in the reality of how millions of developers actually use RunPod to experiment, train, and deploy AI.

Key facts

What you'll do

Build tooling, extensions, and plugins that improve the developer experience on RunPod, and instrument them so the impact is measurable, ensuring each shipped tool demonstrates clear adoption and drives downstream product usage.

Deliver talks at developer and AI developer conferences, and proactively build relationships with organizers and attendees to establish RunPod as a thought leadership platform in AI infrastructure.

Spend dedicated time building as our users build, then surface pain points and bugs you encounter so product and engineering teams can prioritize fixes based on real usage.

Design and run programs that scale our core pillars of content, events, and community, creating durable systems and repeatable processes rather than one-off campaigns.

Show up consistently where developers already gather, build genuine relationships, and translate insights into actionable feedback for Product and other internal teams.

Create technical content such as demos, documentation, tutorials, and sample applications that resonate with a technical audience and lower the barrier to adopting RunPod.

Contribute to open-source ecosystems related to ML, AI frameworks, SDKs, and tooling, leaving a visible footprint that reinforces RunPod's commitment to the broader developer community.

Use your background in GPU compute and ML infrastructure to author workflows that reflect how advanced AI engineering teams actually run and scale models.

Regularly attend in-person events and conferences to represent RunPod, network deeply, and bring back qualitative insights that shape platform decisions.

Speak publicly on behalf of a developer-facing product with clarity and confidence, translating complex platform capabilities into narratives that help developers succeed.

Pass a background check as a condition of employment, ensuring you can represent RunPod professionally in all external engagements.

Ship small, iterative releases of tools and content that validate hypotheses quickly and enable data-driven decisions about future investments.

Identify onboarding friction and gaps in framework support, then create independent solutions that improve time-to-first-success for new developers.

Maintain a high standard of technical communication, ensuring that code samples, demos, and written content are accurate, reproducible, and up to date.

Requirements

Experience writing code in Python, JavaScript, or Go is essential, as you will be building real tools and demos directly on the platform.

Hands-on experience as a software engineer is required so that you can empathize with developers, understand implementation details, and credibility build technical content.

You must be technically credible, able to build and demo real things on the platform, and sustain deep technical conversations without relying on a script.

A track record of creating technical content such as demos, documentation, tutorials, or sample applications tailored to developer audiences is required.

Demonstrated experience building integrations or contributing to open-source projects within an ecosystem of ML/AI frameworks, SDKs, and tooling is mandatory.

Comfort with high autonomy is required, including identifying friction points, prioritizing work, and shipping fixes without waiting for explicit direction.

Familiarity with GPU compute, ML infrastructure, or AI engineering workflows is expected given the technical audience you will serve.

You must be able to regularly attend in-person events and conferences to represent RunPod and gather insights from the community.

The ability to speak publicly on behalf of a developer-facing product is required, including presenting at meetups, webinars, and industry conferences.

Successful completion of a background check is mandatory for this role.

Nice to have

A strong written voice, with recaps and posts that make people who were not in the room feel like they missed a key moment or insight.

The ability to create videos with a high level of technical depth, showing platform workflows, debugging sessions, and advanced use cases.

Familiarity with AI libraries and frameworks, agent frameworks, or ML infrastructure and GPU workloads, so that your contributions accelerate adoption among practitioners.

Practical notes

This is a full-time remote role based in the United States. You must be able to regularly attend in-person events and conferences as part of the role. The work demands high autonomy, ownership, and consistent public representation of RunPod in technical forums.