Developer Relations - Enterprise AI

Lambda; United States; Remote; USD 150,000 - 190,000; Full time

Job summary

Lambda, The Superintelligence Cloud, is hiring a technical practitioner to join Developer Relations and help enterprise teams deploy production AI workloads on Lambda. You will turn deployment experience into useful public resources and leverage your network to reach enterprise AI practitioners who do not hear from Lambda today.

Presence in our San Francisco or San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Qualifications

• 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.

Responsibilities

• Grow Lambda’s reach among enterprise AI and infrastructure practitioners.
• Develop projects with practitioners, customers, or partners. 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 the same ideas through talks and workshops. Use video when it suits the subject, and adapt 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 that evidence to help set Developer Relations priorities.

Skills

Production AI workloads

MLOps

Observability

AI infrastructure

Technical writing

Public speaking

Enterprise networking

Tools

Lambda Cloud

Open-source demos

Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

*Note: 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.

We’re 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.

What You’ll Do

Audience and Distribution

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. Plan distribution through the channels their audiences already use.

Technical Education

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 the same ideas through talks and workshops. Use video when it suits the subject, and adapt strong work for more than one audience.

Field Feedback

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 that evidence to help set Developer Relations priorities.

Experience

• 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 Have

• 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.

What success looks like

More enterprise AI practitioners know and trust Lambda. Lambda is cons