How to apply for IT Systems Engineer, Mobile Client Platform Engineer

About Anthropic

Anthropic is a frontier AI research and product company with teams working on alignment, policy, and security. It posts specific opportunities it considers high impact and explicitly notes it does not necessarily recommend working at other positions there. Candidates should read the linked 80,000 Hours career review about doing harm by working at a frontier AI lab before applying.

About the role

This is an IT systems engineer role on the Endpoint team (Client Platform Engineering), which manages employee laptops and handsets plus the infrastructure underneath them. The fleet is treated as a distributed platform, with configuration shipped as code through pull requests, CI, staging, and a canary group. The role exists to replace today's BYOD mobile setup with a corporate-issued mobile device program in every region Anthropic operates, taking it from early design to production.

A typical day

The job description does not describe a daily routine, and the team is lean and runs with high autonomy, so the actual day-to-day is not specified. Ask the hiring team how the Endpoint team splits design, logistics, and config-as-code work, and what the on-call or support expectations are.

Who Anthropic is looking for

• Has designed or run a corporate-issued mobile device program, including managed company phones and managed Apple accounts.
• Has owned global hardware logistics: procurement partners, regional coverage, spares, and refresh cycles.
• Has shipped configuration as code through pull requests, CI, staging, and canary rollouts, not through manual device setup.
• Can work with high autonomy on a deliberately lean team and define platform decisions rather than follow an existing playbook.

Tips for this application

• Read the 80,000 Hours career review linked in the job post and be ready to state your own position on working at a frontier AI lab.
• Address the BYOD-to-corporate-issued transition directly. Describe a program you designed or ran, including device standards and who gets what.
• Give concrete examples of configuration shipped as code through pull requests, CI, staging, and canary groups. Name the tools.
• Show global logistics experience: procurement partners, regional coverage, spares, and refresh cycles. Include regions and scale.
• Note that the job description is truncated. Ask the recruiter for the full responsibilities list before writing your materials.

What to cover in your cover letter

Describe a corporate mobile device program you took from early design to production. Explain how you decided device standards and what to issue to whom. Show how you handled global procurement, regional coverage, spares, and refresh cycles. Explain how you ship mobile configuration as code through pull requests, CI, staging, and a canary group.

Research before applying

• Read the 80,000 Hours career review on working at an AI lab, linked in the job post, and form a clear position on it.
• Read Anthropic's stated mission: reliable, interpretable, and steerable AI systems that are safe and beneficial.
• Look at Anthropic's published work and teams in alignment, policy, and security to understand the company's scope.
• Check where Anthropic operates so you can speak concretely about regions for the mobile rollout.

Likely interview topics

Based on the job description, expect questions about:

• How you would design a corporate-issued mobile device program from scratch: device standards, what to issue to whom, and regional rollout order.
• How you would run global hardware logistics: procurement partners, regional coverage, spares, and refresh cycles.
• How you ship mobile configuration as code through pull requests, CI, staging, and a canary group, and how you handle a bad canary.
• How you would migrate a BYOD fleet to corporate-issued devices without disrupting employees.
• Your view on working at a frontier AI company, including the concerns raised in the 80,000 Hours career review linked in the post.

Common mistakes to avoid

• Treating the fleet as a collection of individual devices. The team treats it as a distributed platform.
• Describing mobile device management as manual setup or one-off configuration instead of code shipped through pull requests, CI, staging, and canary groups.
• Ignoring the concerns about working at a frontier AI lab that the job post itself links to.