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Lambda is hiring a technical practitioner for Developer Relations to help enterprise teams understand how to deploy production AI workloads on Lambda's cloud infrastructure platform. You will create technically sound educational content, represent Lambda at conferences and in communities, and translate field feedback into product and go-to-market improvements.
Key Responsibilities:
Audience & Distribution: Grow Lambda's reach among enterprise AI and infrastructure practitioners by leveraging your existing following and professional relationships. Develop projects with practitioners, customers, or partners and plan distribution through channels their audiences already use.
Technical Education: Create guides, demonstrations, and open-source examples about deploying production AI workloads on Lambda. Collaborate with machine learning engineers and engineering teams to turn field patterns into useful resources. Deliver talks, workshops, and video content adapted for multiple audiences.
Field Feedback & Community: Represent Lambda at conferences, podcasts, and online communities. Track problems enterprise teams raise, share patterns with Lambda's technical and go-to-market teams, and use evidence to help set Developer Relations priorities.
Success Metrics: Enterprise AI practitioners increasingly know and trust Lambda. Your technical work is accurate and useful for deployment decisions. Your following and collaborations amplify reach in key communities. Practitioner feedback shapes product priorities and gives Lambda clearer visibility into enterprise deployment needs.
Note: This position requires presence in the San Francisco or San Jose office 4 days per week; Tuesday is Lambda's designated work-from-home day.
Requirements:
- Experience deploying and operating production AI workloads, ideally within an enterprise
- Working knowledge of MLOps and observability, including reliability and performance work for AI systems
- Understanding of how internal AI infrastructure supports applications and adoption across organizations
- Demonstrated record of writing or speaking clearly about AI deployment or infrastructure
- Established following or professional network among enterprise AI and infrastructure practitioners
- Experience using collaborations and community relationships to increase reach of technical work
- Ability to work effectively with technical teams, 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 external partner programs
