IT Systems Engineer, Enterprise SaaS

Remote World
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Shift work
Languages
English
Experience level
Senior

Job location

Remote

Tech stack

Microsoft Excel
API
Computing Platforms
Systems Engineering
Software as a Service
Cloud Computing
Code Review
Collaborative Software
Computer Programming
System Configuration
Continuous Integration
Data Governance
Data Migration
Identity and Access Management
Information Technology Operations
Python
OAuth
OpenID
Software Safety
Security Assertion Markup Language (SAML)
Systems Integration
Information Technology
Deployment Automation
Gsuite
Api Management

Job description

The Enterprise SaaS team owns the collaboration and productivity platforms every person at Anthropic touches every day - Google Workspace, Slack, and the surrounding ecosystem of enterprise tools. We're responsible for tenant-wide architecture, API-level integration, and the governance that keeps these platforms secure and scalable as the company doubles and doubles again.

You'll make the architecture decisions that shape how thousands of people work: data governance for collaboration content, the application side of SSO and SCIM provisioning, and the integrations that fill gaps the vendors left open. You'll write Python against SaaS APIs where the admin console stops, and you'll be the final escalation tier when the vendor docs stop helping. The scope is the full collaboration stack - cloud infrastructure and endpoints live with separate teams, so this role goes deep rather than wide.

If you've hit the ceiling of what the admin console can do and started solving problems in code, this is that job. You'll partner closely with IT Operations, Security, and the IAM team on the identity and access layer everything else depends on. This role is high-autonomy: you'll define tenant architecture, write the integrations, and represent the SaaS platform across IT. Your work will directly shape how we scale to AI Safety Level 4 and beyond., * Own tenant-wide architecture for Google Workspace, Slack, and core collaboration platforms

  • Design compartmentalization and data-governance models that scale with the company
  • Build integrations and automation against SaaS APIs to automate provisioning and catch drift
  • Configure the application side of SSO connections and SCIM attribute mappings
  • Serve as the final escalation tier for platform issues Support can't resolve
  • Lead vendor relationships - roadmap influence, escalation paths, engineering-level dialogue
  • Partner with Corporate Security on SaaS hardening, third-party app governance, and compliance controls
  • Own platform configuration as code - auditable, repeatable, and version-controlled, * Programming against SaaS APIs and SaaS API integrations
  • Google Workspace administration
  • Slack administration and APIs
  • Identity protocols (SAML, OAuth, OIDC, SCIM)
  • Enterprise collaboration platform architecture
  • Security and compliance frameworks

Requirements

  • Have 8+ years building secure IT systems in complex environments
  • Excel at solving ambiguous problems with multiple stakeholders
  • Communicate technical concepts clearly to any audience
  • View IT Engineering as requiring product engineering rigor
  • Successfully deliver complex projects from conception to production
  • Write clear documentation as a natural part of your workflow
  • Have deep, hands-on experience with enterprise administration of Google Workspace and Slack
  • Have built integrations against SaaS APIs, not just configured through consoles
  • Have been the final escalation tier, * Have transformed traditional IT operations into engineering-driven organizations
  • Have built strong partnerships with Security and Engineering teams
  • Practice modern development methods (code reviews, testing, CI/CD)
  • Work effectively in distributed teams
  • Have experience with Infrastructure as Code approaches to SaaS configuration
  • Have designed data governance or access controls for collaboration platforms
  • Have experience with SCIM provisioning and SSO federation from the application side
  • Have participated in M&A initiatives and led post-acquisition tenant consolidation - merging collaboration platforms, reconciling identity, migrating data, Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

About the company

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems., We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

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