Engineering Manager, Data Architecture

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.

As the Engineering Manager for Data Architecture, you will lead the team responsible for building our north star implementation of data infrastructure. This team owns the full lifecycle of Anthropic’s most critical data, ranging from customer-facing data like prompts and exchanges (highly PII) to core business data such as logging and financial records. Your mission is to grow this infrastructure into a world-class platform that powers our rapidly expanding business while maintaining the highest standards for AI safety and regulatory compliance.

This is a high-leverage leadership role where you will architect systems that support model training with customer consent, legal reviews, and AI safety evaluations (Safe Guard). You will ensure our data platform is inherently secure, massively scalable, and flexible enough to support diverse product surfaces across multiple cloud environments. If you are passionate about building the foundational systems that enable a frontier AI lab to scale safely and efficiently, this role is for you.

Key Responsibilities

• Build and lead the team: Recruit and mentor a team of world-class data and infrastructure engineers; establish the team’s technical vision, operational standards, and strategic roadmap.

• Drive technical strategy: Define the long-term architecture for Anthropic’s data stack, ensuring it supports high-velocity model training and complex inference workloads across all cloud regions.

• Architect scalable pipelines: Lead the design and implementation of robust, automated data pipelines that handle petabyte-scale datasets with high reliability and performance.

• Implement robust governance: Build the systems and processes for automated data discovery, lineage tracking, and lifecycle management to ensure high data quality and integrity.

• Security and compliance-by-design: Ensure data architecture inherently supports global privacy regulations and security requirements through automated controls and privacy-preserving architectures.

• Cross-functional enablement: Partner with ML, Product, and Legal teams to unlock the power of data, providing the tools and platforms needed to derive insights without compromising safety.

• Standardize data quality: Define and enforce SLAs for data availability and accuracy, building internal tools to monitor and maintain the health of the entire data ecosystem.

• Evangelize the data mission: Advocate for the importance of modern data architecture as a core component of AI safety, communicating progress and risks to leadership and cross-functional stakeholders.

We are looking for a technical leader who combines deep systems engineering expertise with a passion for building scalable data organizations. The ideal candidate has:

• Extensive experience managing and scaling engineering teams in high-growth environments, with a focus on data infrastructure or distributed systems.

• Deep technical expertise in data modeling, database internals, and large-scale data warehouse/lakehouse architectures.

• Proven track record of architecting cloud-native, scalable data platforms that handle multi-cloud deployments and high-throughput data streams.

• Strong foundation in data governance principles, including metadata management, data lineage, and automated quality enforcement at scale.

• Ability to thrive in high-ambiguity environments, translating broad business goals into specific technical roadmaps and actionable engineering tasks.

• Pragmatic approach to engineering: you know when to build for the future and when to deliver immediate value through iterative improvements.

• Excellent communication skills, with the ability to explain complex architectural trade-offs to both technical and non-technical partners.

• Comfort with end-to-end ownership and a desire to build a "full-stack" data foundation that serves as the company's single source of truth.

• 8+ years of experience managing technical teams

• Experience growing an engineering team and charter through a period of rapid company scaling.

• Experience conducting privacy reviews, threat modeling, and risk assessments for production systems

• Proven track record of designing and implementing privacy infrastructure serving millions of users

• Experience at companies during periods of hypergrowth where you've scaled privacy alongside the business

• Exposure to AI/ML infrastructure and the unique privacy demands of large-scale training and inference

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.

$405,000—$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.