IT Systems Engineer, Mobile Client Platform Engineer

• Design the corporate-issued mobile device program: device standards, what we issue to whom, and how the program grows from a first region to everywhere Anthropic operates
• Own the global logistics of issuing hardware: procurement partners, regional coverage, spares, and refresh cycles
• Bring mobile configuration into the team’s config-as-code pipeline so mobile policies are reviewed, tested, and progressively rolled out like the rest of the fleet
• Build zero-touch enrollment: Apple Business Manager and ADE with managed Apple accounts on iOS, the zero-touch equivalent on Android, so a new phone works the first time without hands-on setup
• Own policy, compliance, and device lifecycle for the corporate fleet, from issue to wipe
• Build telemetry on the corporate fleet: which devices are checking in, OS and patch state, drift between reported and actual state
• Own managed app distribution for mobile, from app approval through update rollout
• Partner with Corporate Security on device posture, device trust signals, and travel devices for international trips
• Decide how corporate-issued and BYOD coexist, and own that boundary as the program rolls out

You may be a good fit if you

• Have owned a global or multi-region mobile device program end to end, with 8+ years managing corporate fleets at thousands-of-devices scale
• Go deep on iOS device management: enrollment flows, Apple Business Manager and ADE, APNs and certificate lifecycle, declarative device management
• Have worked with Android device management and can hold your own in a mixed fleet
• Treat device configuration as code and have moved past clicking in consoles
• Have run the infrastructure under an MDM, not just administered a SaaS console: a self-hosted MDM server, AWS, Terraform, and configuration that ships as code
• Have built or launched a corporate device program, not just operated one, and can decide how it coexists with BYOD
• Excel at ambiguous problems that touch several teams at once
• Communicate technical concepts clearly to any audience
• View IT Engineering as requiring product engineering rigor
• Write clear documentation as a natural part of your workflow

Strong candidates may also

• Have managed ChromeOS devices alongside a mobile fleet
• Have run a device program across multiple regions and dealt with the logistics that come with it
• Have built automated, progressive rollout systems with promotion gated on telemetry
• Bring proficiency in Swift for building device tooling
• Have used LLMs to automate operational work, or are excited to make Claude a teammate

• Python and shell scripting
• iOS and Android platform internals (depth on iOS, working knowledge of Android)
• Modern MDM or UEM platforms (Jamf, Intune, Workspace ONE, or equivalent)
• Running the infrastructure under an MDM (self-hosted servers, AWS GCP, Terraform)
• Querying live device state at fleet scale
• Mobile device lifecycle automation (enrollment, policy, patching, app distribution)
• GitOps and CI for configuration management
• Endpoint security fundamentals, 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.

Pulled from the full job description

• Parental leave
• Flexible schedule, Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates’ AI Usage: Learn about our policy for using AI in our application process.

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., The Endpoint team (Client Platform Engineering) manages the laptops and handsets every Anthropic employee works on, plus the infrastructure underneath them. We treat the fleet as a distributed platform, not a collection of devices, and every piece of configuration ships as code through pull requests, CI, staging, and a canary group. Today the mobile side of the fleet is BYOD. This role exists to change that. You will design and implement a corporate-issued mobile device program (managed company phones and managed Apple accounts) in every region Anthropic operates in, and take it from early design to production.

The team is deliberately lean and runs with high autonomy. You’ll define what a corporate mobile program looks like at Anthropic and own the platform decisions that get it there., 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.