Anthropic
AI Engineer, GTM Claudification
About this role
Build and operate autonomous AI agents that power Anthropic's go-to-market operations, from initial prototype through production. You'll develop evaluation frameworks, design human oversight systems, and architect shared platforms while working closely with sales teams to ground agent designs in real workflows.
What you'll do
- Design and deploy autonomous agents for sales motions including inbound, outbound, and pipeline management
- Develop evaluation frameworks and run behavioral benchmarks in development and production environments
- Build MCP servers, agent skills, and web applications integrating with CRM and revenue systems
- Establish human oversight mechanisms including approval gates, handoffs, and escalation paths
- Instrument production systems to measure agent impact on pipeline and revenue metrics
- Architect shared codebases and set technical conventions for go-to-market builders across the org
What they're looking for
- Python or TypeScript production development
- LLM systems architecture and agent development
- MCP server development and tool use design
- Evaluation frameworks and LLM benchmarking
- SQL and data analysis
- CRM and sales engagement systems
- Full-stack web application development
- ML experimentation and A/B testing
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Anthropic
Anthropic builds Claude, an AI assistant, and is hiring for engineering roles across infrastructure, data systems, and security that support both AI research operations and the company's internal technology needs. The company seeks infrastructure engineers, systems integrators, data scientists, and security specialists to build production-scale systems for training data pipelines, financial operations, developer productivity measurement, research infrastructure, and server firmware security.
- Website
- anthropic.com
Likely interview questions
- Walk us through a production LLM system you built—what was your approach to evaluation, and how did you identify and fix problems?
- Describe your experience building MCP servers or similar tool integrations. How did you ensure reliability and governance?