Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
API
Audit
Communication @ 7
Distributed Systems @ 6
Fraud @ 4
IaC
LLM @ 4
Observability
Python @ 6
Rust @ 4
Security
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic is seeking software engineers to help build safety and oversight mechanisms for AI systems. As part of the Safeguards team, the engineer will develop systems that monitor models, prevent misuse, and support user well-being. The role focuses on detecting unwanted model behaviors, preventing disallowed model use, and enforcing terms of service and acceptable use policies.
Responsibilities
- Develop monitoring systems to detect unwanted behaviors from API partners and potentially take automated enforcement actions.
- Surface monitoring results in internal dashboards for analyst review.
- Deploy and operate monitoring systems across multiple cloud providers, including partner environments where data must remain in place.
- Maintain consistent deployments through shared deployment pipelines, smoke tests, observability, and alerting.
- Design and harden sandboxed runtimes for AI agents, including 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 workloads.
- Define and meet service-level objectives for the platform.
- Partner with engineers and researchers developing and evaluating monitoring agents, as well as security, privacy, and legal teams, to ship detection capabilities quickly on a trusted platform.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or comparable experience.
- Proficiency in Python, distributed systems, and infrastructure as code.
- Experience working across multiple cloud providers or building provider-agnostic infrastructure.
- Experience building and operating large-scale distributed infrastructure, such as data platforms, control planes, or job schedulers.
- Experience with sandboxing and isolation technologies, including containers, microVMs, or network policy, or experience with a systems programming language such as Rust.
- Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Additional Qualifications
- 8+ years of experience in a software engineering position.
- Experience building systems that handle sensitive or regulated data with requirements for access control, auditability, retention, and data residency.
- Experience running LLM-based agents in production.
- Experience with integrity, spam, fraud, or abuse detection and mitigation.
Compensation
- Annual salary: $320,000–$485,000 USD.
Work Policy and Sponsorship
- Hybrid policy: Staff are expected to work from one of Anthropic's offices at least 25% of the time, although some roles may require more office time.
- Anthropic sponsors visas for eligible roles and candidates and provides assistance through an immigration lawyer.
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