Research Engineers, Agents

Key Responsibilities

• Design, prototype, and implement agentic AI systems that perform reliably across complex enterprise workflows
• Build compound AI architectures that combine planning, tool use, retrieval, memory, evaluation, orchestration, and execution
• Investigate how agents reason, coordinate, recover from errors, and interact with external systems under real-world constraints
• Create evaluation frameworks that measure agent behavior, task completion, reliability, robustness, and failure modes
• Develop tools and abstractions that make agent behavior easier to observe, debug, test, and improve
• Partner with AI Researchers to explore new agent architectures and with AI Engineers to harden successful approaches for production use
• Integrate agents into customer APIs, applications, data platforms, and operational workflows
• Communicate clearly with internal teams and customer stakeholders about agent capabilities, limitations, tradeoffs, and risks

Who You Are

• Experience Building Agentic Systems: You have built AI systems that use models, tools, retrieval, planning, memory, or multi-step execution to complete real tasks
• Strong Engineering Fundamentals: You write clean, maintainable Python and are comfortable debugging complex, stateful systems
• Systems-Level Reasoning: You think holistically about how prompts, tools, context, evaluators, state, orchestration, and external APIs interact
• Research-Oriented Builder: You are curious about why agents succeed or fail, and you can design experiments to test different architectures and behaviors
• AI-Native Working Style: You use AI tools daily to write code, debug systems, explore designs, analyze traces, and accelerate experimentation
• Bias Towards Showing vs. Telling: You prefer working demonstrations, traces, evaluations, and production behavior over abstract descriptions
• Comfort in Customer Environments: You can translate ambiguous business workflows into concrete agent designs and explain system behavior clearly to stakeholders
• Ownership Mentality: You take responsibility for whether an agentic system performs reliably, safely, and usefully in production

What We Offer

• The base salary range for this role is $150K – $250K, depending on experience, location, and level
• In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
• 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible time off
• Retail and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources
• Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot
• Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems
• Ownership of high-impact projects across top enterprises
• A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence