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.
If you'd like to build the world's best AI cloud, join us.
*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.
About this role
The Superintelligence Technical Success Engineer is part of Lambda's Superintelligence business unit, dedicated to our largest, most strategic customers operating in the most complex environments. This role owns taking signed deployment from contract to a live, fully operational production environment. The role requires strong technical acumen to validate the build against what was promised, spot gaps, and work effectively with engineering and infrastructure teams to get issues resolved and requirements clearly understood.
You'll work alongside the account team, to make sure the customer's requirements and expectations are clearly understood and addressed throughout deployment. This role calls for someone who's ready to dive in wherever the engagement needs them.
What You'll Do
Take signed deployments, from contract, to live, to working production environments, validating configuration, connectivity, storage, and compute against what was promised
Bring technical depth to validation and troubleshooting conversations — asking the right questions, spotting gaps, and working closely with engineering and infrastructure teams to drive issues to resolution
Coordinate with Infrastructure, Engineering, Product, and Data Center teams to close technical dependencies and resolve blockers
Own a current, accurate technical picture of the deployment — what's built, what's open, what's at risk
Keep stakeholders informed with clear, regular status updates: RAG status, top risks, and what's being done about them
Guide the customer through onboarding to their first successful production workload
Be the customer's go-to technical contact through deployment and early production
Feed recurring technical patterns back into reusable runbooks, checklists, or automation
Transition out once the customer is stable and self-sufficient, keeping the broader account team informed along the way
You
4+ years of hands-on technical experience with GPU/HPC infrastructure, cloud platforms, Kubernetes, or large-scale Linux systems
Comfortable being the technical voice in the room able to validate builds, spot gaps, and hold engineering teams accountable for resolving them
Strong troubleshooting instincts and a willingness to get into the weeds of networking, storage, or compute issues
Track record of coordinating across engineering and infrastructure teams to close out technical dependencies
Clear written and verbal communication for status updates and technical documentation
A bias toward diving in and taking ownership, rather than waiting for a fully defined process
Nice to Have
Exposure to large-scale GPU cluster deployments
Familiarity with project/program tracking tools and structured status reporting
Experience building runbooks or checklists that outlived the engagement they were built for
Salary Range Information
The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
About Lambda
Founded in 2012, with 500+ employees, and growing fast
Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
Our values are publicly available: https://lambda.ai/careers
We offer generous cash & equity compensation
Health, dental, and vision coverage for you and your dependents
Wellness and commuter stipends for select roles
401k Plan with 2% company match (USA employees)
Flexible paid time off plan that we all actually use
Equal Opportunity Employer
Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Skills Required
- 4+ years of hands-on technical experience with GPU/HPC infrastructure, cloud platforms, Kubernetes, or large-scale Linux systems
- Ability to validate technical builds, identify gaps, and hold engineering teams accountable for resolution
- Strong troubleshooting skills involving networking, storage, or compute issues
- Experience coordinating across engineering and infrastructure teams to resolve technical dependencies
- Clear written and verbal communication for status updates and technical documentation
- Demonstrated ownership and willingness to work in undefined or evolving processes
- Exposure to large-scale GPU cluster deployments
- Familiarity with project or program tracking tools and structured status reporting
- Experience building reusable runbooks or checklists
What We Do
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure and the #1 GPU Cloud for ML/AI teams. Their mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence.
