Research Engineers, Agents

Posted 15 Days Ago
2 Locations
Hybrid
150K-250K Annually
Entry level
Artificial Intelligence • Software
The Role
Research Engineers design, prototype, evaluate, and productionize agentic AI systems for complex enterprise workflows. They build architectures involving planning, tool use, retrieval, memory, orchestration, and execution; develop evaluation and observability frameworks; investigate reliability and failure modes; integrate agents with customer APIs and data platforms; and communicate capabilities, risks, and tradeoffs to technical teams and stakeholders.
Summary Generated by Built In
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

  • 100% coverage of medical, dental, and vision insurance for employee and dependents

  • Flexible time off

  • Retirement 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

  • Complimentary in-office lunches and snacks provided

  • 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

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.

#LI-Hybrid

We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.

Skills Required

  • Experience building agentic AI systems using models, tools, retrieval, planning, memory, or multi-step execution
  • Strong engineering fundamentals and ability to write clean, maintainable Python
  • Ability to debug complex, stateful systems
  • Systems-level reasoning across prompts, tools, context, evaluators, state, orchestration, and external APIs
  • Research-oriented ability to design experiments testing AI architectures and behaviors
  • Regular use of AI tools for coding, debugging, design exploration, trace analysis, and experimentation
  • Preference for working demonstrations, traces, evaluations, and production behavior
  • Ability to translate ambiguous business workflows into concrete agent designs
  • Ability to explain system behavior clearly to customer stakeholders
  • Ownership of reliable, safe, and useful production agentic systems
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The Company
HQ: San Francisco, California
45 Employees

What We Do

Distyl AI is on a mission to create the most customer-centric AI company that revolutionizes how enterprises thrive in the AI-assisted economy. We collaborate with leading institutions worldwide to enhance their AI readiness and build dependable, seamlessly integrated AI-driven solutions tailored to their distinct data, workflows, and employee requirements. Using our proprietary platform of in-house tools and alliances such as the one with OpenAI, our team diligently develops and deploys generative AI products that adhere to the highest standards of integrity and reliability, empowering the institutions that require them the most.

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