Research Engineers, Agents
External
Distyl · San FranciscoPrepare for this interview
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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
- Develop evaluation frameworks that measure agent behavior, task completion, reliability, robustness, and failure modes
- Create 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
Requirements
- 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: Y ou take responsibility for whether an agentic system performs reliably, safely, and usefully in production
Benefits
Additional Information
About Distyl AI Distyl is an applied AI technology company partnering with the world's most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations - both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations - from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.
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