Technical Success Engineer

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

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

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.

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

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.