Research Engineers, Agents

Distyl AI

$150K — $250K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience building AI systems with agentic capabilities
  • Proficient in writing clean, maintainable Python code
  • Strong understanding of systems-level interactions and orchestration
  • Research-driven with the ability to design and conduct experiments
  • Daily use of AI tools for coding and experimentation
  • Ability to communicate effectively with both technical teams and customers
  • Proven ownership mentality for system performance and reliability

Responsibilities

  • Design and implement agentic AI systems for enterprise workflows
  • Build complex AI architectures integrating multiple functionalities
  • Investigate interactions and behaviors of agents under real-world constraints
  • Develop measurement frameworks for agent performance and reliability
  • Create debugging tools for agent behavior observation and improvement
  • Collaborate with AI Researchers and Engineers to refine and deploy systems
  • Integrate AI agents into customer workflows and applications
  • Communicate system capabilities and limitations to stakeholders

Benefits

  • 100% coverage for medical, dental, and vision for employees and dependents
  • 401(k) plan with additional benefits like commuter perks and in-office lunch
  • Access to cutting-edge AI models and tools for real-world applications
  • Opportunities to lead high-impact projects in leading enterprises
  • Fast-paced, mission-driven work culture emphasizing curiosity and excellence
Full Job Description
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% covered medical, dental, and vision for employees and dependents
  • 401(k) with additional perks (e.g., commuter benefits, in-office lunch)
  • Access to state-of-the-art 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 prizes 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

Similar Jobs

More Jobs at Distyl AI

More Enterprise Technology Jobs

Find similar Research Engineers, Agents jobs: