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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
Join Anthropic's Languages Team as a Python foundational member shaping how Python is used across one of the world's fastest-growing AI companies. We're looking for a Python expert to help define and build the development ecosystem that powers the future of AI development.
You'll be responsible for the full lifecycle of how Python is used by engineers and researchers across Anthropic—from research experiments to production systems serving millions. This includes building foundational language infrastructure, defining best practices, creating tooling, and ensuring exceptional developer productivity while supporting both cutting-edge AI research and massive-scale deployment.
Working at the intersection of the Python ecosystem and AI development, you'll tackle uniquely complex problems where your architectural decisions directly impact how thousands of engineers develop AI systems safely and efficiently. The infrastructure you build must support diverse workloads—from experimental research code to battle-tested production systems—all while maintaining the highest standards of safety, performance, and developer experience.
This is an opportunity to establish the standards and foundations for how Python enables AI development at unprecedented scale, working alongside some of the brightest minds in AI research and engineering.
Responsibilities:
- Design and build foundational Python infrastructure that supports both AI research workflows and production-scale systems
- Define and implement Python ecosystem standards, best practices, tooling, libraries, and frameworks that ensure safety, performance, and exceptional developer productivity across diverse AI workloads
- Establish Python-specific CI/CD pipeline integration, testing frameworks, and deployment strategies optimized for AI development cycles
- Partner extensively with infrastructure teams to ensure seamless integration between Python tooling and broader platform services, such as debugging Kubernetes issues, optimizing node instance types for performance, and collaborating on cross-cutting infrastructure challenges
- Collaborate closely with research and engineering teams to understand emerging requirements and translate them into robust, scalable Python infrastructure, including cross-language interoperability solutions (particularly with Rust)
- Drive technical strategy for Python ecosystem evolution as Anthropic scales, while mentoring engineers and researchers on Python best practices
- Lead incident response and troubleshooting for Python-related issues across research and production environments
You may be a good fit if you:
- Have 5+ years of production software engineering experience with deep expertise in Python
- Have strong experience in developer tooling, build systems, dependency management within a monorepo environment
- Are comfortable working across the stack, including debugging infrastructure issues like Kubernetes problems or optimizing system performance
- Have strong communication and collaboration skills to work effectively with diverse teams including researchers, engineers, and infrastructure specialists
- Are excited about defining foundational systems and processes and are comfortable working independently on ambiguous, high-impact technical challenges
Strong candidates may have:
- Rust experience—we use Rust alongside Python, and familiarity with Python-Rust interop (e.g., PyO3, maturin) is a significant plus
- Built core Python infrastructure like interpreters, package ecosystems, typing tools, or maintained widely-used open-source Python developer tools with significant adoption
- Expertise in Python performance optimization, including experience with Cython, profiling tools, or optimizing Python runtimes
- Experience with AI/ML research-to-production workflows, understanding the unique challenges of supporting both experimental research code and production model training/serving pipelines
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Logistics
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.
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
