Technical Success Engineer
- United States
- Mid Level
- 4+ years
- Posted
Skills
Required
- networking / storage / compute
- GPU/HPC infrastructure
- cloud platforms
- Kubernetes
- Linux systems
- GPU cluster deployments
Preferred
- close technical dependencies
- validate builds
Join Lambda's Superintelligence business unit as a Technical Success Engineer. In this role, you will take signed deployments from contract to a live, fully operational production environment. You will work closely with engineering and infrastructure teams to resolve issues and ensure customer requirements are met. This position requires strong technical acumen and a willingness to dive in wherever needed. Benefits include health, dental, vision, 401k match, flexible PTO, and paid parental, medical, and caregiver leave.
Experience building runbooks or checklists that outlived the engagement they were built for
Responsibilities
- Take signed deployments from contract to live, validating configuration, connectivity, storage, and compute against what was promised.
- Coordinate with Infrastructure, Engineering, Product, and Data Center teams to close technical dependencies and resolve blockers.
- Guide the customer through onboarding to their first successful production workload, being the customer's go-to technical contact.
- Clear written and verbal communication for status updates and technical documentation
- Track record of coordinating across engineering and infrastructure teams to close out technical dependencies
- Comfortable being the technical voice in the room able to validate builds, spot gaps, and hold engineering teams accountable for resolving them
- Familiarity with project/program tracking tools and structured status reporting
Requirements
- 4+ years of hands-on technical experience with GPU/HPC infrastructure, cloud platforms, Kubernetes, or large-scale Linux systems
- A bias toward diving in and taking ownership, rather than waiting for a fully defined process
- Strong troubleshooting instincts and a willingness to get into the weeds of networking, storage, or compute issues
- Exposure to large-scale GPU cluster deployments
Pay
USD 214,000 - 285,000
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