Staff+ Software Engineer, Safeguards Data

Anthropic; New York (NY); Hybrid; USD 320,000 - 485,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation and parental leave

Flexible working hours

Office space for collaboration

Job summary

Anthropic in New York, NY, is seeking a software engineer for the Safeguards team to build data pipelines and governance controls for our AI safety systems. You will deploy across AWS, GCP, and Azure, monitor models, and prevent misuse while upholding safety and transparency.

The role emphasizes data correctness, access controls, and portability, with collaboration across analysts and researchers in a fast-growing environment.

Qualifications

• Proficiency in Python and SQL.
• Experience building and operating data pipelines or data stores in production.
• Ability to work across the data stack: ingestion, storage, consumption.
• Strong written and verbal communication skills to explain tradeoffs.

Responsibilities

• Build and operate the data platform powering Safeguards.
• Keep Safeguards systems running with high operational standards.
• Own data governance, retention, access controls and privacy handling.
• Design portable systems across cloud providers.
• Collaborate with analysts, investigators, and researchers relying on the data.

Skills

Python

SQL

Data pipelines

Data stores

Communication skills

Education

Bachelor's degree

Tools

AWS

GCP

Azure

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 AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.