Research Engineer, Agents

Position Overview

• Location Type: Remote
• Employment Type: Full-time
• Salary: Not specified

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:

Agentic systems are the next frontier of usefulness for Claude. Over the last year, we’ve seen rapid adoption of Claude-powered agentic systems in spaces like coding, research, customer support, network security, and more. We believe this is just the beginning, and we expect Claude to be handling much more complex tasks end-to-end or in cooperation with a human user as time goes on. We have a team striving to make Claude an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, memory, and inter-agent coordination. This team endeavors to maximize agent performance by solving challenges at whatever level is needed, whether it’s finetuning, agent infrastructure, or agent design best practices.

Given that this is a nascent field, we ask that you share with us a project built on LLMs that showcases your skill at getting them to do complex tasks. Here are some example projects of interest: design of complex agents, quantitative experiments with prompting, constructing model benchmarks, synthetic data generation, model finetuning, or application of LLMs to a complex task. There is no preferred task; we just want to see what you can build. It’s fine if several people worked on it; simply share what part of it was your contribution. You can also include a short description of the process you used or any roadblocks you hit and how to deal with them, but this is not a requirement.

Responsibilities

• Finetune new capabilities into Claude that maximize Claude’s performance or ease of use on agentic tasks
• Ideate, develop, and compare the performance of different tools for agents (eg memory, context compression, communication architectures for agents)
• Systematically discover and test prompt engineering best practices for agents
• Develop automated techniques for designing and evaluating agentic systems
• Assist with automated evaluation of Claude models and prompts across the training and product lifecycle
• Work with our product org to find solutions to our most vexing challenges applying agents to our products
• Help create and optimize data mixes for model training
• Help to create and maintain the infrastructure required for efficient prompt iteration and testing.

Requirements

• Significant ML and software engineering experience
• At least a high level familiarity with the architecture and operation of large language models
• Extensive prior experience exploring and testing language model behavior

Application Instructions

• Share a project built on LLMs that showcases your skill at getting them to do complex tasks. (Examples provided in the description)