Staff+ Software Engineer, Safeguards Data

Anthropic · Safeguards (Trust & Safety)

支持签证Anthropic H-1B 获批 76 次 (FY2025)英国签证担保名单$320k–$485k/年New York City, NY发布 2026-08-14
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Visa sponsorship:  We do sponsor visas!

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职位描述 Job description

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 support user well-being. This role focuses on the data foundations that make that work possible: the pipelines, stores, and governance controls that our detection, evaluation, and review systems are built on, deployed across AWS, GCP, and Azure. 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.

The systems you build sit underneath decisions with real consequences for customers and for people affected by model misuse, and much of the data moving through them is sensitive. Correctness, retention discipline, and access control are core engineering requirements here rather than things bolted on afterward. You will also design for portability from the outset, because these systems run in customer-managed and third-party environments you do not fully control.

Key responsibilities

Build and operate the data platform that powers Safeguards, including ingestion and processing pipelines, warehouses and other data stores, and the schemas and interfaces that detection and review systems depend on

Keep Safeguards systems running day to day and hold a high operational bar that serves both safety and customers, while reducing the manual effort needed to sustain it

Own data governance and integrity, including retention and access controls, privacy-preserving handling of sensitive data, lineage, and correctness guarantees that downstream consumers can rely on

Design systems that run portably across cloud providers, working within the constraints of customer-managed and third-party environments

Partner with the analysts, investigators, and researchers who rely on this data, and build the internal tooling their work depends on

Minimum qualifications

Proficiency in Python and SQL

Experience building and operating data pipelines or data stores in production

Ability to work across the data stack, including ingestion, storage, and consumption

Strong written and verbal communication skills, including the ability to explain technical tradeoffs to people outside your discipline

Preferred qualifications

Extensive experience as a software engineer, including significant time on data-intensive systems

Experience with integrity, spam, fraud, or abuse detection and mitigation

Experience building trust and safety detection and intervention mechanisms for AI or machine learning systems

Experience building and operating large-scale distributed data infrastructure

Experience working across multiple cloud providers, or building infrastructure designed to be provider-agnostic

Experience meeting data governance requirements in a regulated or high-sensitivity domain

Experience working closely with operational teams to build custom internal tooling

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:  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.

Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit  anthropic.com/careers  directly for confirmed position openings.

How we're different

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

原文来自 greenhouse,以官网为准。

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