Developer Relations - Enterprise AI

Lambda•San Francisco, CA

12d•$188,000 - $250,000•Hybrid

About The Position

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers, ranging from AI researchers to enterprises and hyperscalers. Our mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. We are hiring a technical practitioner to join Developer Relations and help enterprise teams understand how to deploy production AI workloads on Lambda. You will turn deployment experience and work from Lambda’s technical teams into useful public resources. Your existing following and professional relationships will help that work reach enterprise AI practitioners who do not hear from Lambda today. This position requires presence in our San Francisco or San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Requirements

Experience deploying and operating production AI workloads, ideally inside an enterprise.
Working knowledge of MLOps and observability, including the reliability and performance work required to keep AI systems running.
An understanding of how internal AI infrastructure supports applications and adoption across an organization.
A record of writing or speaking clearly about AI deployment or infrastructure.
An established following or professional network among enterprise AI and infrastructure practitioners.
Experience using collaborations and community relationships to increase the reach of technical work.
The ability to work effectively with technical teams as well as marketing and customer-facing groups.

Nice To Haves

Experience with on-premises AI infrastructure or internal AI programs used by dozens of people.
Familiarity with Lambda Cloud or 1-Click Clusters.
Experience producing technical video, live demonstrations, workshops, or programs with external partners.

Responsibilities

Grow Lambda’s reach among enterprise AI and infrastructure practitioners.
Use your following and professional relationships to introduce Lambda to communities where it has limited presence.
Develop projects with practitioners, customers, or partners and plan distribution through the channels their audiences already use.
Create technically sound material about deploying production AI workloads on Lambda.
Work with MLE and engineering to turn field patterns into guides, demonstrations, or open-source examples.
Teach ideas through talks and workshops, using video when it suits the subject, and adapting strong work for more than one audience.
Represent Lambda at conferences and on podcasts.
Take part in relevant online communities.
Track the problems enterprise teams raise and share useful patterns with Lambda’s technical teams and go-to-market leaders.
Use evidence from field feedback to help set Developer Relations priorities.