Developer Relations - Enterprise AI

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.

You

• 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 considered more often for production AI workloads.
• Your technical work is accurate and useful to teams making deployment decisions. Your following and collaborations give that work wider reach in the communities that matter to Lambda.
• Feedback from practitioners shapes Developer Relations priorities and gives Lambda’s product teams a clearer view of enterprise deployment needs.