Founding Developer Relations Engineer
Role Overview
Goaly is an early-stage AI startup founded by ex-Meta Superintelligence Labs engineers and researchers.
Goaly is the autonomous performance layer for AI training, watching jobs across a GPU fleet, catching wasteful runs, reallocating compute, and showing model improvement costs.
The product runs on-prem, telemetry-only, and starts read-only.
Goaly is backed by leading AI investors and endorsed by frontier AI researchers and builders.
Key Skills for This Role
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About Goaly AI
Goaly is an early-stage AI startup founded by ex-Meta Superintelligence Labs engineers and researchers.
Goaly is the autonomous performance layer for AI training, watching jobs across a GPU fleet, catching wasteful runs, reallocating compute, and showing model improvement costs.
The product runs on-prem, telemetry-only, and starts read-only.
Goaly is backed by leading AI investors and endorsed by frontier AI researchers and builders.
About The Role
This is the first Developer Relations hire, working closely with the founding team.
The role owns building the Goaly developer community, hosting events, and collecting product feedback.
An engineering background is required to build demos, write quickstarts, and answer technical questions in public.
A customer-first product mindset is required to make developers successful first.
A background in model training is not required.
This is a founding role with no playbook yet and real influence over how Goaly is perceived by the AI developer community.
Build the AI Developer Community
- Stand up and run Goaly's developer community on Discord or Slack and social channels where users are, including X, LinkedIn, Hacker News, and Reddit.
- Be present daily to answer questions, welcome newcomers, triage issues, gather product feedback, and surface what people are building.
- Identify and amplify community contributions, success stories, and creative uses of Goaly.
- Build relationships with influential developers, AI researchers, open-source maintainers, and technical educators and bring them in as early members and collaborators.
Host Events
- Plan and run Goaly's event program end to end, including hackathons, hands-on workshops, Bay Area meetups, office hours, and live coding sessions.
- Own agenda, speakers, logistics, on-site execution, and follow-up for events.
- Represent Goaly at conferences, hackathons, and university recruiting events.
- Land talks at venues users attend, such as PyTorch Conference, MLSys, Ray Summit, GTC, AI Engineer events, and NeurIPS and ICML workshops.
- Turn each event into community growth, product feedback, and pipeline, and track which formats work.
Collect and Route Product Feedback
- Gather feedback from online channels and in-person conversations with users, design partners, and prospects.
- Synthesize feedback into clear, prioritized insight for engineering and product.
- Reproduce problems developers hit, bring precise reports to engineering, and close the loop with the community on what shipped.
- Join design-partner and prospect calls with the GTM team when a technical voice closes the gap.
- Turn repeated questions into docs, demos, or product changes.
Build and Explain
- Build demo applications, sample integrations, and reference setups that show what is possible on Goaly and keep them working as the product evolves.
- Write quickstarts, tutorials, and cookbooks that get a developer from zero to a first result in thirty minutes.
- Partner with engineering to turn every new capability into accessible content the week it ships, including posts, short videos, and live walkthroughs.
- Turn the founding team's experience into talks and posts that the community wants to share.
Own Community Growth
- Track community growth and engagement, event attendance and follow-through, docs funnel, feedback items shipped, inbound design-partner requests, and candidates sourced.
- Double down on what works and kill what does not.
Typical Week
- A day and a half in the community on Discord and GitHub, DMs with developers, welcoming and unblocking people, and writing up what they said.
- A day building a demo app, sample integration, or quickstart, or reproducing a user-reported bug.
- A day on events, planning the next workshop or hackathon, lining up speakers, prepping a talk, or running the event.
- Half a day writing or recording a post, tutorial, or short video.
- A day with the team on engineering feedback, GTM prospect questions, and founder narrative time.
- Roughly 10% travel over the year for conferences, hackathons, and customer visits.
You May Be a Good Fit If You Have
- An engineering background with 1-3 years as a software engineer and 1+ year of AI-native coding experience.
- Ability to build a working demo quickly, read someone else's stack trace, and answer a technical question in public without checking with anyone first.
- Experience building applications with LLMs or AI tooling and shipping something real on top of a model API or AI framework.
- A customer-first product mindset with ability to listen to frustrated engineers and translate technical feedback into product improvements.
- Community building experience with reach you can point to, such as a community you built or grew, events you organized, an audience on X, LinkedIn, YouTube, a newsletter, or GitHub.
- Solid written and oral communication with a track record of explaining technical things clearly in public through posts, docs, talks, tutorials, or videos.
- Self-starter and fast learner who identifies what is missing and drives it without waiting to be asked.
Strong Pluses
- 1-3 years of AI application, solution engineer, or forward-deployed engineer experience taking a customer from a blank page to a result on an AI product.
- Prior developer relations, developer advocate, or community building experience at AI, MLOps, or SaaS companies.
- Experience organizing hackathons, workshops, or meetups and running a developer Discord or Slack.
- Active presence in developer communities such as GitHub, X, Discord, or Reddit and existing relationships with AI engineers, researchers, or open-source maintainers.
- Fluency on video and on stage, comfortable on a podcast or conference keynote.
- Familiarity with ML/AI training workflows or AI stacks such as PyTorch, Ray, Kubernetes, or W&B; helpful, not required.
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