Technical Success Engineer

Lambda; San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health, dental, vision coverage

Wellness stipend

Commuter stipend

401k with company match

Flexible PTO

Job summary

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. 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.

Qualifications

• 4+ years of hands-on technical experience with GPU/HPC infrastructure, cloud platforms, Kubernetes, or large-scale Linux systems.
• Ability to validate builds and hold engineering teams accountable for resolutions.
• Strong troubleshooting and willingness to dive into networking, storage, or compute issues.
• Experience coordinating across engineering and infrastructure teams.
• Clear written and verbal communication for status updates and technical docs.
• Bias toward ownership and initiative.

Responsibilities

• 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.

Skills

GPU/HPC infra

Cloud platforms

Kubernetes

Linux systems

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.

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.