In 2012, Lambda started with a crew of AI engineers publishing research at top machine-learning conferences. We began as an AI company built by AI engineers. That hasn’t changed. Today, we’re on a mission to be the world’s top AI computing platform. We equip engineers with the tools to deploy AI that is fast, secure, affordable, and built to scale. Whether they need powerhouse GPU hardware on-site or the flexibility of cloud-based solutions, we’ve got the horsepower to make it happen. Lambda’s AI Cloud has been adopted by the world’s leading companies and research institutions including Anyscale, Rakuten, The AI Institute, and multiple enterprises with over a trillion dollars of market capitalization. Our goal is to make computation as effortless and ubiquitous as electricity.

If you’d like to build the world’s best deep learning cloud, join us.

• Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

SALARY RANGE INFORMATION

Based on market data and other factors, the annual salary range for this position is $245,000 - $385,000. 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.

• Design and implement full-stack monitoring solutions that provide visibility from the browser to the database
• Create robust CI/CD pipelines for reliable deployments across frontend and backend services
• Develop and maintain API gateway configurations, rate limiting, and API versioning strategies
• Implement SLIs, SLOs, and error budgets that reflect the complete customer experience
• Architect resilient application patterns including circuit breakers, retries, and graceful degradation across the stack
• Build and optimize caching strategies at multiple levels (browser, CDN, API, database)
• Collaborate with development teams to establish full-stack performance benchmarks and testing methodologies
• Create runbooks and automated remediation for common failure scenarios
• Lead incident response for customer-facing application issues and conduct thorough post-mortems
• Optimize resource utilization across web servers, application servers, and database tiers
• Design secure authentication flows and session management with high availability requirements
• Build in automation and auditing to ensure compliance and improve efficiency and productivity
• Implement and integrate logging and metrics across platforms such as Datadog, Prometheus, OpenTelemetry, Grafana, SumoLogic, etc