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Dropzone AI

AI Research Engineer - Senior to Principal-level

AI ResearchUpdated on Nov 13
Full-timeRemote in USA

About the Job

Requirements

  • At least 5 years of software engineering experience, including at least 1 year applying generative AI in production.
  • Proven experience building or researching agent frameworks or tool-using large language models.
  • Proven experience building or researching memory and retrieval systems, including retrieval-augmented generation, vector databases, or hybrid retrieval.
  • Expert Python development skills.
  • Familiarity with OpenClaw and Claude Code harness architecture.
  • Ability to operate effectively in an early-stage startup environment, navigate ambiguity, and execute quickly.

Responsibilities

  • Design and implement advanced multi-step reasoning agents involving tool use, planning, reflection, and self-improvement loops.
  • Develop frameworks for multi-agent coordination and task decomposition.
  • Improve the reliability, latency, and cost efficiency of agent execution.
  • Architect short-term and long-term memory subsystems, including episodic, semantic, retrieval-based, and hybrid systems.
  • Build mechanisms for context compression, retrieval, and grounding.
  • Explore approaches to continual learning and state persistence.
  • Define and implement agent performance evaluation frameworks covering task success, reasoning quality, and robustness.
  • Build automated evaluation pipelines using synthetic data, adversarial testing, and regression testing.
  • Establish metrics and benchmarks for agent reliability in production.
  • Translate current research into production-grade systems.
  • Run experiments, analyze results, and iterate.
  • Contribute to internal knowledge sharing and technical direction.

Desired Qualifications

  • Experience with agent orchestration frameworks such as LangGraph, AutoGen, or custom systems.
  • Experience with abliteration.
  • Familiarity with AI safety guardrails, hallucination mitigation, and structured output enforcement.
  • Experience designing offline and online large language model evaluations, including human-in-the-loop and synthetic-data approaches.
  • Publications or open-source contributions in relevant areas.
  • Experience applying current context and harness engineering techniques to customer-facing products.
  • Founder experience, experience as one of the first 10 employees at an early-stage company, or experience establishing a new technology initiative within a more established company.

About the Company

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