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Software Engineer, Distributed Systems

Job in New York, New York County, New York, 10261, USA
Listing for: EngineersOfAI
Full Time position
Listed on 2026-10-17
Job specializations:
  • Software Development
    DevOps, AI Engineer (Applied/Software), Cloud Engineer - Software, Software Engineer
Salary/Wage Range or Industry Benchmark: 320000 - 485000 USD Yearly USD 320000.00 485000.00 YEAR
Job Description & How to Apply Below
Position: Staff+ Software Engineer, Distributed Systems
Location: New York

About Anthropic

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.

About the role

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.

Responsibilities:
  • 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
You may be a good fit if you:
  • 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

Final date to receive applications: None. Applications will be reviewed on a rolling basis.

The annual compensation 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.

Annual Salary: $320,000 — $485,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study:

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