Domino Data Lab

Domino Data Lab

Staff Performance & Reliability Engineer

Remote US · Staff+

Sponsorship not specified$185k-$210kDetected 29 days ago
PythonDistributed SystemsSnowflakeCloud PlatformsKubernetesPrometheusGrafanaSite Reliability EngineeringPlatform EngineeringLoad Testing

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

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Files H-1B transfers

1 transfer filing in the last year, covering 1 worker. Median labor-condition decision: 441 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake and other leading investors, we have been in business for over a decade but are still a small team operating with the spirit of a startup.
  • For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
  • This salary range will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location.

Responsibilities

  • Diagnose and drive resolution of performance bottlenecks and resource misconfigurations surfaced by scale testing - working directly with platform and infrastructure teams to ship fixes, not just file tickets
  • Deliver accurate, data-driven sizing recommendations for customer-facing documentation based on rigorous empirical testing across deployment sizes
  • Partner with platform teams to enable effective scale and reliability testing across additional cloud providers, helping position Domino for future multi-cloud success
  • Increase the efficiency and leverage of a small team by building infrastructure automation that scales operationally as the product and customer base grow

Requirements

  • Strong proficiency in Python and comfort working in a large, modular codebase that spans orchestration, infrastructure automation, and systems integration
  • Experience with observability stacks (Prometheus, Grafana, New Relic, or similar) - writing queries, building dashboards, and using metrics to diagnose performance and reliability issues at the systems level

Compensation

  • $185,000 - $210,000 USD
  • For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Benefits

  • We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company

Company info

  • At Domino, we build solutions that help the largest, highly regulated organizations adopt AI to accelerate mission-critical use cases. Our platform integrates a streamlined model and app development environment, advanced model, agent, and app hosting capabilities, and novel governance capabilities providing regulator-ready AI at scale. Our customers - like Johnson & Johnson, GSK, Bristol Myers, UBS, FINRA and the US Navy - are using our software to solve some of the most important challenges in the world, such as developing new medicines, securing our financial markets, or protecting our country. Backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake and other leading investors, we have been in business for over a decade but are still a small team operating with the spirit of a startup. In the world of AI today, we believe that the future is still being invented - and we want to be the ones building it. For more information, visit www.domino.ai
  • What we are building
  • The Automation Team at Domino acts as a force multiplier for engineering, building the tools and systems that enable teams to ship code confidently and consistently. A core part of this mission is Tempest, an in-house platform that orchestrates realistic, long-duration workloads against live Kubernetes clusters and validates the results against real observability data. Today, when scale testing surfaces a bottleneck, a resource misconfiguration, or a regression in system behavior, the team can identify and report the issue - but we need someone who can take the next step: profiling services, tracing root causes through Prometheus and New Relic data, and partnering with platform engineers to drive durable fixes. Focused on iteration and continuous improvement, the team looks for targeted enhancements that create outsized impact, and this role will close the gap between detection and resolution at the infrastructure level.
  • What your impact will be
  • At Domino, we build solutions that help the largest, highly regulated organizations adopt AI to accelerate mission-critical use cases.
  • Our platform integrates a streamlined model and app development environment, advanced model, agent, and app hosting capabilities, and novel governance capabilities providing regulator-ready AI at scale.
  • Our customers - like Johnson & Johnson, GSK, Bristol Myers, UBS, FINRA and the US Navy - are using our software to solve some of the most important challenges in the world, such as developing new medicines, securing our financial markets, or protecting our country.
  • In the world of AI today, we believe that the future is still being invented - and we want to be the ones building it.
  • For more information, visit www.domino.ai
  • The Automation Team at Domino acts as a force multiplier for engineering, building the tools and systems that enable teams to ship code confidently and consistently.
  • A core part of this mission is Tempest, an in-house platform that orchestrates realistic, long-duration workloads against live Kubernetes clusters and validates the results against real observability data.
  • Today, when scale testing surfaces a bottleneck, a resource misconfiguration, or a regression in system behavior, the team can identify and report the issue - but we need someone who can take the next step: profiling services, tracing root causes through Prometheus and New Relic data, and partnering with platform engineers to drive durable fixes.
  • Focused on iteration and continuous improvement, the team looks for targeted enhancements that create outsized impact, and this role will close the gap between detection and resolution at the infrastructure level.
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This listing is sourced directly from Domino Data Lab's careers page and normalized into a canonical job model.