Lead Software Development Manager - Remote
•Jobgether· 14h
EngineeringFull-timeAmericas
14h ago
Anthropic·1 day ago
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 a Data Engineer on the Economic Research team, you will build, maintain and lead the critical data engineering that powers Anthropic's research on AI's economic impact. You will work with data systems from across Anthropic, including our research tools for privacy-preserving analysis. You will work at the intersection of data engineering and software engineering.
In this role, you will work closely with teams across Anthropic—including Data Science and Analytics, Data Infrastructure, Clio Engineering, Societal Impacts, and Public Policy—to build scalable and robust data systems that support high-leverage, high-impact research. Your work will enable economists and researchers—both internal and external—to understand how AI is transforming economic activity. You will have an opportunity to shape the direction of data foundations for economic research at Anthropic during a period of fast growth.
Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.
Expand privacy-preserving tools to enable new analytic functionality to support research needs.
Design and build upon novel data systems leveraging language models (e.g., CLIO) where traditional data engineering patterns don't yet exist.
Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.
Lead the strategic development of the economic research data foundations roadmap
Ensure data reliability, integrity, and privacy compliance across all economic research pipelines and retention runs.
Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.
Collaborate with the broader Data Science and Analytics and Data Infrastructure teams to align on tooling, infrastructure patterns, and shared data resources.
5+ years of experience as a Data Engineer, Analytics Engineer, or Software Engineer working on data engineering or data foundations, with a track record of building and maintaining production systems
Have experience with data infrastructure and large datasets in production environments.
Have experience with cloud infrastructure platforms such as AWS or GCP.
Design, implement and test data models for economic research.
A passion for Anthropic's mission of building helpful, honest, and harmless AI and understanding its economic implications.
Strong programming skills in Python and SQL, with experience building production-quality data pipelines and analytical tools.
Demonstrated ability to translate ambiguous questions into concrete technical requirements and scalable solutions.
A bias for action and urgency, not letting perfect be the enemy of the effective.
A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.
Background in econometrics, statistics, or quantitative social science research
Experience building data infrastructure and data foundations for research
Familiarity with large language models, AI systems, or ML research workflows
Prior work on projects related to labor economics, technology adoption, or economic measurement
The annual compensation range for this role is 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. Our total compensation package for full-time employees includes equity and benefits.
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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. 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.
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.
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