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# Staff+ Software Engineer, Distributed Systems

- **Company:** Anthropic Limited
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $320,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Computer Networks, Data Security, Distributed Systems, Monitoring of Systems, Job Scheduling, Python (Programming Language), Systems Development Life Cycle, Smoke Testing, Software Engineering, Delivery Pipeline, Large Language Models, Agentic-AI, Infrastructure Automation Frameworks, Information Technology, Data Management
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/staff-software-engineer-distributed-systems-new-york-ny--8934378f-e484-4244-ae95-593515cf989e

## About the Role

Software Engineering, Distributed Computing, Artificial Intelligence (AI), Software Engineering, Scalable System Development, Distributed Computing, Production Systems, Reporting Dashboards, Application Programming Interface (API), Smoke Testing, * Bachelor's degree in Computer Science, Software Engineering or comparable experience

 * Proficiency in Python, Distributed Systems, and Infrastructure as Code
 * Have worked across multiple cloud providers, or built infrastructure designed to be provider-agnostic
 * Have built and operated large-scale, distributed infrastructure, such as data platforms, control planes, or job schedulers
 * Have experience with sandboxing and isolation technologies (containers, microVMs, network policy) or with a systems language such as Rust
 * Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders

Strong candidates may also:

 * 8+ years of experience in a software engineering position, not including internships
 * Have built systems that handle sensitive or regulated data, with requirements around access control, auditability, retention, and data residency
 * Have experience running LLM-based agents in production
 * Have experience with integrity, spam, fraud, or abuse detection and mitigation, 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.

## Description

We are looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building distributed and scalable systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies., * Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system

 * Develop monitoring systems to detect unwanted behaviors from our API partners and potentially take automated enforcement actions; surface these in internal dashboards to analysts for manual review
 * Stand up and run deployments of those monitoring systems across multiple clouds, including inside cloud-provider partner environments where data residency laws apply. Keep the deployments consistent through shared deployment pipelines, smoke tests, observability, and alerting
 * Design and harden the sandboxed runtime that AI agents execute in: isolation, network egress controls, least-privilege data access, audit logging, and insider-risk controls
 * Manage cost and capacity for large volumes of long-running agent work, and set and meet service-level objectives for the platform
 * Partner with the engineers and researchers who write and evaluate the monitoring agents, and with security, privacy, and legal teams, so new detection work can ship quickly on a platform everyone trusts