Who we are
At Domino, we build software that helps the largest, AI-driven organizations build and operate advanced data science and AI solutions at scale. Our platform integrates a streamlined model development environment, MLOps capabilities, and novel features for collaboration, reuse, and reproducibility — all of which make data science teams more productive, reduce time to value, and ensure compliance. 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 a decade but are still a small team operating with the spirit of a startup. Especially 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
Our Professional Services team designs and delivers the architectures and integrations that embed Domino into our customers’ IT landscapes. As Solution Architects, we embed Domino into the most complex enterprise IT landscapes on the planet — hybrid cloud, on-prem, air-gapped, regulated — and turn what we see in the field into a sharper product.
What your impact will be
Lead technical execution on Domino's most strategic F100 deployments — multi-cloud, on-prem, and hybrid — powering enterprise AI/ML at scale.
Design end-to-end reference architectures that hold up in regulated environments across data, identity, security, and infrastructure.
Build and document field integrations across the AI/ML ecosystem (data platforms, model registries, MLOps tooling), then enable the rest of Solutions on them.
Partner with account and SE teams on scoping, custom demos, and PoCs that map to real customer AI use cases — not generic ones.
Translate what you see in the field into roadmap input Product and Engineering actually act on.
What we look for in this role
5+ years hands-on with Kubernetes in production — upgrades, migrations, multi-region DR, cluster management at scale.
End-to-end enterprise K8s implementations in the wild, cloud or on-prem (OpenShift a strong signal). PoCs and Terraform-only don't count.
Direct experience owning strategic customer relationships at CTO / platform-lead level, not one step below.
Hands-on with at least one major cloud (AWS, Azure, or GCP) — Azure a strong plus — and comfort translating security and compliance requirements into architectures that pass audit.
Hands-on AI/ML or data platform experience (Domino or comparable MLOps tooling), especially in regulated environments — a strong plus.
What we value
We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply
We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success
We believe in individuals who seek truth and speak the truth and can be their whole selves at work
We value all of you that believe improving is always possible. At Domino, everything is a work in progress – we can do better at everything
We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company
#LI-Remote
The annual US base salary range for this role is listed below. 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. Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.
Compensation Range
$200,000 — $250,000 USD