Full-Time

Staff Software Engineer

Domino Data Lab

Domino Data Lab

201-500 employees

Unified AI model development and governance

Compensation Overview

$200k - $250k/yr

+ Equity + Bonus/Commissions

Remote in USA

Remote

Category
Software Engineering
Required Skills
LLM
gRPC
Kubernetes
Microsoft Azure
Python
Apache Spark
Machine Learning
Java
Docker
AWS
Go
Scala
REST APIs
DevOps
Google Cloud Platform

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Requirements
  • Building Scalable Systems: Hands-on experience developing and managing high-performance back-end systems in distributed computing environments
  • Collaboration Across Teams: Working closely with cross-functional teams to integrate systems with front-end interfaces and third-party services
  • API Development: Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC)
  • Performance Optimization: Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes
  • Testing and CI/CD: Using robust testing frameworks (unit, integration, end-to-end) and setting up CI/CD pipelines
  • Familiarity with traditional machine learning model development and AI workflows, including experiment tracking, hyperparameter optimization, model evaluation frameworks, and managing model artifacts
  • Distributed Computing: Experience with frameworks like Apache Spark, Azure ML, or SageMaker is a plus
  • Cloud Platforms: Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments
  • Back-End Development: Expertise in languages such as Python, Java, Scala, or Go
Responsibilities
  • Build and enhance platform features that enable teams to design, test, and deploy multi-agent workflows at scale
  • Enhance Domino’s Extensions framework for enabling customers to build custom modules that extend platform feature and function
  • Expand the platform's inference infrastructure to support high-throughput, low-latency serving of large language models, helping customers confidently operationalize LLM applications at enterprise scale

Domino Data Lab provides a unified AI platform for building, deploying, and managing AI models across an enterprise. The platform acts as a central hub for AI operations, enabling collaboration, governance, and best-practice workflows while tracking models in production and managing costs. It connects a wide ecosystem of open source and commercial tools and supports running AI workloads close to data on-premises, in hybrid setups, or across multiple clouds to optimize performance, reduce expenses, and ensure compliance. Domino generates revenue by charging businesses for platform access and usage, helping optimize compute and cloud costs, manage AI risk, and automate DevOps to support enterprise-scale AI initiatives.

Company Size

201-500

Company Stage

Series F

Total Funding

$226.6M

Headquarters

San Francisco, California

Founded

2013

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Simplify Jobs

Simplify's Take

What believers are saying

  • Public sector revenue doubled 2025 after $16.5M U.S. Navy contract reduced ML model updates from six months to days.
  • Autoscaling and spot instances deliver up to 60% AI compute cost savings, addressing uncontrolled infrastructure spend in enterprises.
  • 88% of organizations now move AI from experimentation to production, yet 60% see less than 50% ROI, highlighting infrastructure demand.

What critics are saying

  • AWS Bedrock and Azure AI offer native guardrails at zero marginal cost, forcing Domino to fight for default enterprise awareness.
  • Open-source frameworks like LangChain embed native tracing and policy enforcement, making Domino's governance claim redundant and bypassable.
  • Cost tools like AWS Compute Optimizer save 65–70%, outpacing Domino's 60%, making its efficiency pitch uncompetitive in cloud contracts.

What makes Domino Data Lab unique

  • Domino is the first fully governed end-to-end system for agentic AI, with universal tracing and LLM hosting.
  • Platform enables open-source tool access without vendor lock-in, integrating SAS, R, Python across any cloud or on-prem environment.
  • Managed data planes allow secure, localized compute near data, reducing movement costs while meeting sovereignty and compliance requirements globally.

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Benefits

Health & Wellness - Premium medical, dental, and vision insurance plans, including a free option for you and your family.

Commuter Benefits - What’s your transportation of choice? We support your daily commute, whether Uber, Lyft, bus, or train.

Love for parents - New parents receive six weeks of fully-paid parental leave. P.S. Got baby pics? Share them in our Slack channel dedicated to kids.

Flexible Paid Time Off - We value your right to disconnect. Take the time you need to recharge, spend time with family, and explore the world.

Annual Education Reimbursement - Pursue the professional growth that will help you excel in your role with educational opportunities that work for your needs, and at your speed.

Own Your Outcome - Feel supported to get your work done how and when you need to, regardless of your location.

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-1%

2 year growth

-3%
PR Newswire
Feb 26th, 2026
Domino launches end-to-end platform to operationalise enterprise agentic AI systems

Domino Data Lab has launched a platform update creating what it calls the first fully governed end-to-end system for operationalising agentic AI. The Winter Release introduces an agentic development lifecycle experience and LLM hosting capabilities for building, evaluating, deploying and monitoring agentic AI systems at scale. The platform addresses challenges teams face moving agentic AI from prototype to production by providing universal tracing, structured evaluation tools, production-ready deployment capabilities and continuous performance monitoring. New features include built-in instrumentation that traces every step of agentic AI creation and side-by-side comparison tools for evaluating applications. The update also enables organisations to securely host and manage LLMs within their own infrastructure. All features are now available in Domino Cloud, targeting regulated industries including financial services, government and life sciences.

PR Newswire
Feb 5th, 2026
Former Joint Chiefs Vice Chair Admiral Grady joins Domino Data Lab board as public sector revenue doubles

Domino Data Lab has appointed Admiral Christopher Grady, former 12th Vice Chairman of the Joint Chiefs of Staff, to its board as an independent member to guide public sector strategy. The company also promoted Chris Elsins to Global Vice President of Public Sector to lead government business. The appointments follow Domino's public sector revenue more than doubling in the past year. The enterprise AI platform provider recently secured a $16.5 million contract as prime vendor for the U.S. Navy's Project Overmatch, reducing machine learning model update times from six months to days—a 97% decrease. Grady previously commanded U.S. Fleet Forces Command. Elsins will oversee Domino's strategy across federal, defence, intelligence and state agencies as the company scales AI capabilities for critical government missions.

SiliconANGLE Media
Oct 23rd, 2025
Domino Data takes aim at AI costs with autoscaling tools and spot instances

Domino Data takes aim at AI costs with autoscaling tools and spot instances. Data science operations startup Domino Data Lab Inc. today unveiled new capabilities in its popular Domino Cloud platform aimed at boosting the scalability of artificial intelligence applications and agents and make them more cost-effective. Domino Cloud is a software-as-a-service platform that's used by developers from companies such as Bayer AG and Moody's Corp. to prepare datasets for machine learning projects and automate tasks such as deploying AI models and monitoring their performance. The platform also provides comprehensive tools for AI governance, ensuring that neural networks work reliably and don't expose sensitive data to unnecessary risks. During model development, it analyzes them for potential data breaches and other risks. Another key component is Domino Apps, which provide interactive tools for users to share and run AI applications and agents without extensive knowledge of DevOps practices. Domino Apps is the focus of today's update, which recognizes that many enterprises struggle to create value from their AI deployments due to an inability to scale them to support real-world use cases. It's also designed to address "uncontrolled infrastructure spend," which stems from the underutilization of compute resources, maintenance and excessive data movement, the company said. To get around these problems, Domino said it's introducing a new autoscaling capability in Domino Apps, plus a new compute grid tool to help customers get a handle on the spiraling production costs of AI. The new autoscaling tools are meant to make AI more easily consumable for business users and will ensure that every new app and AI agent scales seamlessly. The platform will automatically dedicate more compute and storage resources as each one's user base grows, without incurring unnecessary costs from underutilization. In addition, there's a new application discovery tool in Domino Apps, which can help workers to find existing apps and agents that may be relevant to their workflows. The idea is to facilitate greater consumption and help organizations squeeze more value out of their AI investments, the company said. To ensure companies can keep a lid on their AI infrastructure costs, Domino is adding support for spot instances, enabling users to access compute resources for AI development, training and inference on demand, with cost savings of up to 60%. Spot instances are incredibly useful, because while they tend to be a bit more expensive, most cloud providers try to encourage companies to pay upfront to reserve instances, which leads to those resources being underutilized. To aid further in cost-cutting, Domino said it's now managing all customer data via data planes in the Domino Cloud platform. Its data plane technology serves as the execution layer for running and scaling AI and allows each single-tenant Domino Cloud environment to run securely across multiple geographic regions. As a result, customers can bring their compute resources closer to the data that powers their AI applications and agents, reducing data movement costs while simultaneously addressing any data sovereignty requirements they need to abide by. Constellation Research Inc. analyst Holger Mueller said Domino seems to have gotten its priorities right. Today's updates, he said, recognize that whoever can help enterprises to build AI applications faster and run them more cost-effectively is likely going to be successful. "It's good to see a startup like Domino making inroads here, giving enterprises the ability to auto-scale their AI applications and use spot instances to run ad hoc workloads," he said. "This is just the kind of thing enterprises want and need to accelerate AI adoption." Domino co-founder and Chief Executive Nick Elprin said the updates address key pain points for customers, who have expressed that while "AI experimentation is easy, finding value is much harder." The company said the new capabilities are rolling out for Domino Cloud on Amazon Web Services first of all, with support for additional cloud platforms, such as Google Cloud and Microsoft Azure, to come in upcoming releases. Image: siliconangle/meta AI. A message from John Furrier, co-founder of SiliconANGLE: Support its mission to keep content open and free by engaging with theCUBE community. Join theCUBE's Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities. * 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more * 11.4k+ theCUBE alumni - Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network. SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE, theCUBE Network, theCUBE Research, CUBE365, theCUBE AI and theCUBE SuperStudios - with flagship locations in Silicon Valley and the New York Stock Exchange - SiliconANGLE Media operates at the intersection of media, technology and AI. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Its new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.

FinSMEs
Aug 22nd, 2025
UBS Invests in Domino Data Lab

Domino Data Lab, a San Francisco, CA-based provider of an enterprise AI platform, received an investment from UBS

SiliconANGLE Media
Jun 18th, 2025
Domino Data Lab introduces new AI governance, data management features

Domino Data Lab Inc. today introduced new features for managing artificial intelligence models and the data they process.