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.

What We Are Looking For

At Distyl, Research Engineers build the bridge between frontier AI research and production systems that deliver real business value. This role is for engineers who are excited to investigate how AI systems should be designed, rapidly prototype new ideas, and turn promising concepts into reliable systems that work inside real customer environments.

Research Engineers operate at the intersection of applied research, systems engineering, and customer-facing deployment. They design and implement compound AI systems, run experiments to understand system behavior, build evaluation frameworks, and collaborate closely with AI Researchers, AI Engineers, and customer stakeholders. Their work is not limited to demos or isolated prototypes: they help turn new techniques into robust systems that can be measured, operated, and improved in production.

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

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

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