---
title: 'Technical Cloud Operations Lead at Domino Data Lab'
canonical: 'https://feeny.ai/job/technical-cloud-operations-lead-domino-data-lab-argentina-e9eqaetsaezd'
type: 'job'
last_seen: '2026-09-09'
---

# Technical Cloud Operations Lead at Domino Data Lab

- **Company:** Domino Data Lab
- **Location:** Argentina
- **Work type:** remote
- **Posted:** 2026-09-03
- **Last confirmed live:** 2026-09-09
- **Apply:** https://app.careerpuck.com/job-board/domino-data-lab/job/8176952?gh_jid=8176952

## Job description

## 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

The Cloud Operations team at Domino is building the operating capability that helps us safely and reliably manage a growing fleet of customer cloud environments.

As Domino's cloud footprint grows, we want routine production operations to become increasingly standardized, observable, and easy to execute safely. Cloud Operations sits at the intersection of Customer Experience, Platform Services, Support, and SRE, taking ownership of the day-to-day operating system around cloud changes while partnering with engineering teams to continually improve the underlying tooling.

This is a founding role with an opportunity to shape how the function works. You will help turn recurring production work into clear, repeatable operating paths; identify where better tooling or automation can remove operational friction; and create a model that can scale without requiring engineering involvement in every routine change.

What your impact will be

- Establish and help shape Domino's Cloud Operations capability, creating clear ownership and operating practices for routine production changes across our cloud environments.
- Build an initial service catalog for our most common operations, with clear procedures, risk boundaries, verification steps, rollback paths, and escalation points.
- Take hands-on ownership of appropriate cloud operations and recurring campaigns while ensuring work is carried through verification and completion.
- Reduce the amount of routine operational work that requires ad hoc involvement from Platform Services and SRE engineers.
- Partner closely with Platform Services, SRE, and Support to identify recurring friction and turn it into improvements in automation, tooling, documentation, and self-service.
- Improve visibility into how Cloud Operations is performing through useful measures such as operational volume, exceptions, verification time, engineering escalations, and paved-road coverage.
- Help build the operational controls and evidence practices needed as Domino supports increasingly complex and regulated customer environments.
- Leave the service easier to operate than you found it: recurring problems should increasingly become standardized, automated, delegated, or eliminated rather than simply handled faster.

## What we look for in this role

- Experience working with production cloud or SaaS environments in roles such as Cloud Operations, Production Operations, Site Reliability Engineering, Platform Operations, DevOps, Application Operations, or a similar technical operations function.
- Familiarity with cloud-native technologies and concepts. Experience with AWS and Kubernetes is especially useful, but we care more about your ability to understand production systems and make sound operational decisions than expertise in every technology we use.
- Experience taking recurring or loosely defined operational work and helping make it more structured, documented, and repeatable.
- Strong operational judgment: you can follow a known path confidently, recognize when reality no longer matches the procedure, and know when to stop, investigate, or involve an engineering partner.
- Comfort using logs, monitoring, deployment output, configuration, and other technical signals to understand the state of a system and communicate effectively with the engineers who build it.
- A systems mindset. You look beyond solving today's request and ask whether repeated work can be simplified, standardized, automated, or avoided altogether.
- Strong ownership and follow-through, including attention to verification, documentation, and closure after a production change has been executed.
- Ability to collaborate across engineering and customer-facing teams, make unclear ownership visible, and help turn operational problems into actionable improvements.
- Clear written and verbal communication, particularly when documenting procedures, explaining risk, coordinating changes, or escalating exceptions.
- You do not need to be a dedicated software or platform engineer. Some scripting or infrastructure-as-code experience is helpful, but this role is primarily about technical operations, sound judgment, service ownership, and continuous improvement.

## 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

## About Domino Data Lab

## Company Overview
- **One-liner**: Domino Data Lab provides an enterprise AI platform that unifies tools, infrastructure, and governance to help organizations build, scale, and govern AI-powered applications.
- **Entity Type**: Private (Series F)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2013
- **Founders**: Nick Elprin (CEO), Christopher Yang, and Matthew Granade

## Core Business
- **Primary industry**: Enterprise AI / MLOps / Data Science and Machine Learning Platforms
- **Target customers**: B2B, highly regulated enterprises — including 20% of the Fortune 100, such as life sciences, financial services, insurance, and public sector organizations.
- **Mission**: "Unleash AI to address the world’s most important challenges" — helping enterprises accelerate science and research while reducing cost, risk, and complexity.

## Products & Services
- **[Model Factory]**: The core development environment for building AI systems and applications. Supports every method from statistical computing to agentic AI, with any coding assistant, language, or framework. [domino.ai](https://domino.ai/)
- **[Governance Center]**: Govern AI systems and applications to reduce risk and ensure compliance. Defines policies once and enforces them across the entire lifecycle with complete auditability, quality control, and cost visibility. [domino.ai](https://domino.ai/)
- **[App Hub]**: Scale AI-powered applications to thousands of users securely. Delivers governed applications to decision-makers with no rewrites from development to production. [domino.ai](https://domino.ai/)
- **[Agentic AI]**: Design autonomous agents with any framework, deploy them as governed applications, and manage them across their entire lifecycle — all in one platform. [domino.ai](https://domino.ai/)
- **[Coding Assistants]**: Adds traceability, reproducibility, and governance to everything produced by coding assistants. [domino.ai](https://domino.ai/)
- **[Model Risk Management (MRM)]**: A platform for the full model lifecycle, from development through ongoing regulatory compliance, enabling faster model validation with fewer audit findings. [domino.ai](https://domino.ai/)
- **[Document Intelligence]**: Build AI that reads, classifies, and extracts insight from documents at scale, enabling faster decisions from unstructured data at lower cost. [domino.ai](https://domino.ai/)
- **[Statistical Computing Environments (SCE) Solutions]**: A fully reproducible, audit-ready platform for SAS, R, and Python, designed for faster clinical trial submissions with lower compliance risk. [domino.ai](https://domino.ai/)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total Funding — Over $300 million raised (backed by notable investors). The platform is trusted by over 20% of the Fortune 100. [domino.ai](https://domino.ai/company)
- **Notable Investors/Partners**: Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital, and other leading investors. [builtin.com](https://builtin.com/company/domino-data-lab)
- **Growth Signals**: Named to Inc.’s 2026 Best Workplaces list. Recognized in the 2025 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. Customer wins include the U.S. Navy (75% reduction in model deployment time), Moody's (50%+ reduction in deployment time), and UBS (5-year partnership for model risk management). [domino.ai](https://domino.ai/)

## Competitive Advantages
- **End-to-end, unified platform**: Combines development (Model Factory), governance (Governance Center), and deployment (App Hub) into a single platform — a holistic approach that reduces cost, risk, and complexity.
- **Built for highly regulated enterprises**: Domino's governance-by-default design is purpose-built for industries like finance, life sciences, and defense, where compliance and auditability are non-negotiable.
- **Proven impact at scale**: Customers report a 6x reduction in infrastructure costs, a 50% reduction in end-to-end model lifecycle time, 40% faster model development, and 75% faster model deployment. [domino.ai](https://domino.ai/)
- **Reproducibility by default**: Every experiment, model, and decision is captured automatically, allowing teams to reproduce any result without manual reconstruction — a critical moat in regulated environments.

## Strategic Focus
- **Agentic AI and AI-powered applications**: Domino is heavily investing in enabling agentic AI workflows and the deployment of AI-powered applications at scale, as evidenced by their new "Agentic AI" and "App Hub" product lines.
- **Deepening governance and compliance**: The "Governance Center" and "Model Risk Management" solutions indicate a strategic focus on making compliance a core feature, not an afterthought, for enterprise AI.
- **Industry-specific solutions**: Targeting specific verticals like life sciences (SCE solutions), financial services (MRM), and defense (U.S. Navy collaboration) to create tailored, high-value offerings.

## Why Work Here
- **Impact-driven mission**: Employees work on solving "the world’s most important problems" — from developing new medicines and more efficient crops to building safer defense systems.
- **Flexible work environment**: Domino operates a hybrid workspace with "flexible" on-site time. They have offices in San Francisco, London, and a remote hub in Argentina. The company states: "Feel supported to get your work done how and when you need to, regardless of your location." [builtin.com](https://builtin.com/company/domino-data-lab)
- **Generous benefits**: Premium medical, dental, and vision insurance (with a free option for family), competitive parental leave, flexible paid time off, annual education reimbursement, and commuter benefits. [domino.ai](https://domino.ai/careers)
- **Culture of ownership**: The company values "low ego and a high degree of ownership," seeking "self-starters" who can "own your outcome." [domino.ai](https://domino.ai/careers)
- **Award-winning workplace**: Domino was named to Inc.’s 2026 Best Workplaces list, signaling strong employee satisfaction and culture. [domino.ai](https://domino.ai/company)
- **Global team with 200+ employees**: A growing, mid-sized company where employees can feel the direct impact of their work. [builtin.com](https://builtin.com/company/domino-data-lab)

## Sources
1. [domino.ai](https://domino.ai/)
2. [domino.ai/company](https://domino.ai/company)
3. [domino.ai/careers](https://domino.ai/careers)
4. [builtin.com](https://builtin.com/company/domino-data-lab)
5. [linkedin.com](https://www.linkedin.com/company/domino-data-lab)

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