Jobs / United States / Domino Data Lab INC

Domino Data Lab INC

Staff Performance & Reliability Engineer

Remote US · Remote Posted 22 days ago

Apply on company site ↗ Source: Company careers site Tailor my CV

Free account: one tailored CV and cover letter included. You always apply on the employer’s own page.

Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 3 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Domino Data Lab INC paid sponsored hires in similar roles2 certified filings for “Software Engineer II” (Software Developers) in CA: $165k–$170k, median $168k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 3 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Domino Data Lab INC paid sponsored hires in similar roles
2 certified filings for “Software Engineer II” (Software Developers) in CA: $165k–$170k, median $168k. Most were filed at wage level II (50%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

Who we are 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 In your first year, you will: • Serve as the technical owner of Tempest, Domino's scale and reliability platform, ensuring it remains reliable, extensible, and aligned with evolving infrastructure needs • 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 • Strengthen observability across scale testing by improving Prometheus and New Relic instrumentation, making it faster to pinpoint root causes during and after multi-day load runs • Establish and operationalize scale testing on cloud platforms, ensuring appropriate sizing and configuration guidance for this increasingly divergent product line • 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 What we look for in this role • Background in SRE, platform engineering, or infrastructure with hands-on experience operating and troubleshooting distributed systems in production Kubernetes environments • 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 • Demonstrated a

Apply on company site ↗