---
title: 'Staff Software Engineer, IDSM at Domino Data Lab'
canonical: 'https://feeny.ai/job/staff-software-engineer-idsm-domino-data-lab-us-canada-rn2kz3x1ez0h'
type: 'job'
last_seen: '2026-10-14'
---

# Staff Software Engineer, IDSM at Domino Data Lab

- **Company:** Domino Data Lab
- **Location:** US Canada, Argentina
- **Compensation:** $200k–$235k
- **Work type:** remote
- **Posted:** 2026-10-07
- **Last confirmed live:** 2026-10-14
- **Apply:** https://app.careerpuck.com/job-board/domino-data-lab/job/8230498?gh_jid=8230498

## 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

Domino’s Identity and Access platform (IDSM) is the foundation for how customers in some of the world’s most regulated industries manage who can see and do what. We’re evolving it into a centralized, relationship-based authorization framework built on SpiceDB, and you’d be the technical anchor for its next phase.

- A unified authorization model. Extend a centralized, fine-grained, relationship-based model across the platform, replacing feature-specific permission checks with consistent, reusable primitives.
- Production-grade operations. Harden the authorization layer for the scale, reliability, and security that enterprise and public-sector customers expect.
- A thoughtful migration path. Make the sequencing and design calls that let us retire legacy access checks without disrupting customers along the way.
- Groups and organizations that mirror real customers. Rethink how we model groups and organizational hierarchies so large enterprises can represent their teams the way they actually work.
- Cloud-native identity. Deepen integration with cloud workload identity, starting with AWS IRSA and extending to Azure and GCP equivalents.
- Foundations other teams build on. Design core identity and access capabilities, with clean interfaces and flexible abstractions, that engineers across the company can adopt with confidence.
- A stronger way of building. Set the patterns for how the team uses AI-assisted development to ship high-quality features faster, without compromising security or code quality.

What your impact will be

- Set the architectural direction. Design identity and access solutions that meet customer demands for managing user and group access, and are secure, scalable, and built on primitives teams can reuse.
- Bring clarity to complex decisions. Articulate the architecture clearly enough that the rest of Engineering can rally around it.
- Be the go-to authority. Engineers and teams building on IDSM will bring their auth questions to you, and your technical judgment will carry real influence.
- Raise the engineering bar. Lead design reviews, unblock engineers facing ambiguity, and champion flexible abstractions and well-thought-out interfaces.
- Increase velocity and reduce maintenance. Improve our architecture, including removing tech debt, so the team ships faster with less ongoing maintenance.
- Shape how we build with AI. Establish patterns for using AI-assisted development to deliver high-quality features faster without compromising security or rigor.
- Foster ownership and urgency. Help the team know what to build and value both quality and speed of iteration and contribute to experiences that make identity and user management easier for the enterprises we serve.

## What we look for in this role

## Experience

- A track record of evolving an enterprise-grade authorization system under real production traffic, with strong opinions about the architecture of these systems
- Experience designing a new auth system and migrating to it from a legacy approach (a plus)
- Experience on a platform team supporting other services within a larger engineering organization
- A background at a company that builds authentication or authorization products (a plus)
- A concrete example of an auth system you helped build that solved a recurring class of customer challenges
- A history of helping teams become better engineers by improving designs, velocity, and quality

## Skills

- Authorization systems: Hands-on experience with relationship-based or fine-grained authorization, including schema design (relations, permissions, caveats) and the tradeoffs versus traditional RBAC
- Identity protocols: Solid grounding in OIDC and SAML, and ideally experience with an IdP such as Keycloak, Auth0, Okta, or ForgeRock
- Cloud identity: Practical experience with workload identity patterns such as AWS IRSA, Azure Workload Identity, or GCP Workload Identity Federation
- Secrets management: Familiarity with a credential management system such as Vault
- Backend engineering: Strong Go, Java, or a comparable language, comfort running services on Kubernetes, and API design instincts from owning a platform others build on
- System architecture: Experience architecting auth frameworks that scale to enterprise customers
- AI-assisted development: Considered, real-world experience using AI coding tools while maintaining code quality and security rigor

## What We Value

- 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
- 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

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—$235,000 USD

#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—$235,000 USD

## 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)

## Other roles at Domino Data Lab

- [Solution Architect](https://feeny.ai/job/solution-architect-domino-data-lab-united-states-qz3a5a1ew8rg) — United States
- [Forward Deployed Engineer](https://feeny.ai/job/forward-deployed-engineer-domino-data-lab-new-york-2wn91zhttk6b) — New York, NY
- [Forward Deployed Engineer, Life Sciences](https://feeny.ai/job/forward-deployed-engineer-life-sciences-domino-data-lab-barcelona-01vber1azarz) — Barcelona, Spain
- [Forward Deployed Engineer, Life Sciences](https://feeny.ai/job/forward-deployed-engineer-life-sciences-domino-data-lab-berlin-rp47rqqp3nq5) — Berlin, Germany
- [Software Engineer, Intern - Campus Recruiting 2027](https://feeny.ai/job/software-engineer-intern-campus-recruiting-2027-domino-data-lab-new-york-yd54ed27phgf) — New York, NY
- [Forward Deployed Engineer, Intern - Campus Recruiting 2027](https://feeny.ai/job/forward-deployed-engineer-intern-campus-recruiting-2027-domino-data-lab-new-york-nghjdcdrhqe0) — New York, NY
- [Software Engineer - New Grad, 2027](https://feeny.ai/job/software-engineer-new-grad-2027-domino-data-lab-new-york-q2brhm8hwwn4) — New York, NY
- [Forward Deployed Engineer - New Grad, 2027](https://feeny.ai/job/forward-deployed-engineer-new-grad-2027-domino-data-lab-new-york-j3yv62ngtevw) — New York, NY
- [Technical Cloud Operations Lead](https://feeny.ai/job/technical-cloud-operations-lead-domino-data-lab-argentina-e9eqaetsaezd) — Argentina
- [IT Support Engineer](https://feeny.ai/job/it-support-engineer-domino-data-lab-india-eu-south-sq761rmx3bbg) — India EU South, United States