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The role involves leading a team of analytics engineers to develop scalable data solutions for product metrics, ensuring data integrity, and fostering a culture of excellence in data-driven decision making.

Software engineers at Anthropic will develop safety mechanisms, monitor AI systems, and build abuse detection infrastructure to enhance user well-being and prevent misuse.

Build and scale AI-based monitoring systems that analyze very large unstructured datasets, produce trustworthy structured insights, and enable human oversight. Work across the stack from core analysis frameworks to user-facing tools, partner with researchers and safety teams, develop agentic integrations for autonomous investigation, and shape team strategy and tooling investments.

As an Analytics Engineer, you will create scalable solutions for data reporting, build data pipelines, and establish high data integrity standards while collaborating with multiple teams.

Oversee development and execution of enterprise-focused events aimed at pipeline generation and customer relations, collaborating with sales, partnerships, and marketing teams.

The role involves building and improving systems for training AI models, focusing on algorithms and infrastructure for reinforcement learning. Responsibilities include enhancing performance, reliability, and usability of systems to support research.

Lead training on Claude Code for go-to-market teams, develop technical content, deliver live training, and gather feedback for continuous improvement.

Lead identification, pursuit, negotiation, and compliance of federal, state, and local tax and non-tax incentives for infrastructure investments. Manage incentive portfolios, prepare applications and agreements, coordinate cross-functional stakeholders, maintain post-award compliance, monitor policy developments, and build relationships with government and utility partners.

The Research Scientist will develop AI capabilities for life sciences tasks, create evaluation benchmarks, and build tools for biological workflows using machine learning to enhance research outcomes.

As part of the Safeguards Data Science team, you will analyze user behavior, define success metrics, and foster a data-driven culture to improve AI safety.