Developer Relations

About us

Gimlet is building the first multi-silicon neocloud designed for fast, efficient AI inference.

We combine large-scale compute infrastructure with an execution platform that partitions AI workloads and maps each stage to the hardware best suited to run it.

We work with foundation labs, hyperscalers, and AI-native companies, giving our team access to technical problems spanning frontier models, production infrastructure, and emerging hardware.

About the role

Gimlet Labs is seeking an AI Developer Advocate to help developers discover, evaluate, and successfully build on our AI inference platform.

You’ll sit at the intersection of engineering, product, and community. You’ll create technically credible demos and educational content, engage directly with AI builders, and turn their feedback into improvements across our APIs, SDKs, documentation, and product experience.

This is a hands-on technical role for someone who enjoys building in public, explaining complex systems clearly, and helping developers move from their first API call to reliable production deployments.

Developer advocacy is not simply promotion. The role succeeds when developers trust our technical guidance, enjoy building with the platform, and see their needs reflected in the product.

You should be equally comfortable writing code, teaching a technical concept, talking with a developer who is stuck, and explaining to an internal team why a particular piece of developer friction matters.

What success looks like

In the first 6 months, you will:

Identify the best channels for Gimlet’s developer outreach and build initial presence

Build trusted relationships within relevant AI developer communities.

Ship useful examples and educational content that developers actively adopt.

Established a reliable feedback loop between developers and the product team.

Set an objective for developer experience on our upcoming developer cloud offering

You may be a good fit if you have

Evidence of technical communication, including articles, talks, videos, documentation, open-source projects, or sample applications.

Strong empathy for developers and an instinct for recognizing friction in APIs, documentation, and tooling.

The ability to explain technical subjects clearly to audiences with different levels of expertise.

Comfort engaging publicly and representing a technical product.

The ability to operate independently in a fast-moving environment.

Hands-on experience building applications with LLM or multimodal-model APIs.

A practical understanding of AI inference concepts such as latency, throughput, context length, batching, quantization, model routing, and cost.

Professional software development experience, ideally with Python or TypeScript.

Strong candidates may also have

Experience with open-weight models and serving frameworks such as vLLM, SGLang, or TensorRT-LLM.

Familiarity with agent frameworks, retrieval systems, evaluations, observability, and fine-tuning.

Experience running workshops, hackathons, developer programs, or technical communities.

Contributions to open-source AI projects.

Experience working in developer relations, developer experience, solutions engineering, or developer education.

Familiarity with GPU infrastructure and production ML systems.

Why join now?

Gimlet is expanding from its core technology into a production neocloud spanning new hardware, customers, and data centers.

Solve hard problems.

Own meaningful work.

Build for production.

Help define what’s next.

Agency Policy: Gimlet Labs does not accept unsolicited resumes from recruitment agencies or search firms. Any unsolicited resumes submitted without a signed agreement will be considered the property of Gimlet Labs, and no fees will be paid.