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Senior Infrastructure Software Engineer
2 months ago
Position Overview:
Anthropic Limited is on the lookout for skilled and seasoned Infrastructure Engineers to enhance our efforts in developing, scaling, and maintaining innovative AI systems. This role presents an exciting opportunity to engage with advanced AI technologies and contribute to the evolution of state-of-the-art models, aligning with Anthropic's vision of fostering safe and dependable AI systems that serve humanity.
Current Opportunities Available:
- Data Infrastructure: The Data Infrastructure team is tasked with architecting, constructing, and sustaining the data frameworks that drive our AI research and products. Collaborating with diverse teams, you will assess data needs, deliver robust and efficient data solutions, and perpetually refine our data infrastructure. Your responsibilities will include constructing and enhancing data pipelines, enforcing data governance best practices, monitoring and resolving issues, and establishing technical strategies for scalable, dependable data systems and pipelines. Familiarity with technologies such as Spark, Airflow, dbt, and cloud services from GCP and AWS will be essential, alongside designing processes that promote effective team operations and continuous enhancement.
- Research Infrastructure: The research infrastructure team focuses on creating and scaling systems that empower researchers to iterate swiftly and ensure that key systems/components utilized during the development phase can operate at production scale as our model footprint expands.
- Site Reliability Engineering: As a Site Reliability Engineer at Anthropic, you will devise and implement scalable solutions, partner with development teams to enhance infrastructure reliability, and set up monitoring systems, Service Level Objectives (SLOs), and Service Level Indicators (SLIs). You will adopt fault-tolerant design patterns, develop automation tools, and participate in an on-call rotation. By employing Infrastructure as Code (IaC) principles, you will collaborate with cross-functional teams to guarantee reliability and scalability in new features and services, thereby accelerating engineering reliability through superior tooling.
- Systems: The systems team is accountable for managing some of the largest and most intricate clusters in the industry, utilized for training, researching, and ultimately serving AI models. Your contributions will be vital in ensuring Anthropic's capability to reliably and safely train advanced models. You will be responsible for constructing systems and operating extensive Kubernetes clusters with GPU/TPU/Tranium workloads.
- Observability: The observability team is responsible for designing, building, and maintaining the observability infrastructure that guarantees the reliability, performance, and efficiency of our AI systems and services. You will work with various teams to comprehend their observability needs and deliver solutions utilizing technologies such as Prometheus, Splunk, Cloud Logging, Grafana, and Honeycomb. Your role will involve creating a configuration-driven approach to manage dashboards and alerts, implementing structured logging and tracing, optimizing the observability stack, and developing a reliable system that requires minimal maintenance. You will promote a culture of operational excellence, proactive monitoring, and continuous improvement by providing managed, centralized, and user-friendly observability tools.
Key Responsibilities:
- Lead the development of industry-leading AI clusters (ranging from thousands to hundreds of thousands of machines), collaborating closely with cloud service providers on cluster development and necessary features.
- Engage with various stakeholders to thoroughly understand infrastructure, data, and compute requirements, identifying potential solutions to support advanced research and product development.
- Establish technical strategies and oversee the development of high-scale, reliable infrastructure systems.
- Mentor top technical talent within the organization.
- Design processes (e.g., postmortem reviews, incident response, on-call rotations) that enhance team effectiveness and prevent repeated failures.
- 8+ years of relevant industry experience, with at least 3 years leading large-scale, complex projects or teams as an engineer or technical lead.
- A strong passion for distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement.
- Proficiency in at least one programming language (e.g., Python, Rust, Go, Java).
- Excellent problem-solving skills and the ability to work independently.
- A commitment to supporting internal partners, such as research teams, to understand their needs.
- Outstanding communication skills to build consensus with stakeholders, both internally and externally.
- In-depth knowledge of modern cloud infrastructure, including Kubernetes, Infrastructure as Code, AWS, and GCP.
- Expertise in security and privacy best practices.
- Experience with machine learning infrastructure, including GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL.
- Low-level systems experience, such as Linux kernel tuning and eBPF.
- Technical expertise in quickly understanding systems design trade-offs and keeping pace with rapidly evolving software systems.
Application Deadline: Applications will be reviewed on a rolling basis.
