[Remote] AI Research Engineer
Note: The job is a remote job and is open to candidates in USA. Dropzone AI is on a mission to scale cybersecurity through AI augmentation, aiming to enhance the capabilities of human security engineers. They are seeking a Senior to Principal-level AI Research Engineer to lead the design and development of advanced AI systems, focusing on agent architecture, memory engineering, and model evaluation. This role involves translating cutting-edge research into practical applications that improve cyber defense.
Responsibilities
- Design and implement advanced multi-step reasoning agents (tool use, planning, reflection, self-improvement loops)
- Develop frameworks for multi-agent coordination and task decomposition
- Improve reliability, latency, and cost efficiency of agent execution
- Architect short-term and long-term memory subsystems (episodic, semantic, retrieval-based, hybrid)
- Build mechanisms for context compression, retrieval, and grounding
- Explore novel approaches to continual learning and state persistence
- Define and implement evaluation frameworks for agent performance (task success, reasoning quality, robustness)
- Build automated eval pipelines (synthetic data, adversarial testing, regression testing)
- Establish metrics and benchmarks for agent reliability in production
- Translate latest community research ideas into production-grade systems
- Run experiments, analyze results, and iterate quickly
- Contribute to internal knowledge sharing and technical direction
Skills
- 5+ years in software engineering, with at least 1+ year applying GenAI in production
- Proven experience building or researching: Agent frameworks / tool-using LLMs
- Proven experience building or researching: Memory / retrieval systems (RAG, vector DBs, hybrid retrieval)
- Expert Python developer
- Familiar with openclaw and Claude Code harness architecture
- Early-stage startup mindset. You thrive on ambiguity and move with lightspeed execution
- Experience with agent orchestration frameworks (LangGraph, AutoGen, custom systems)
- Familiarity with AI safety guardrails, hallucination mitigation, and structured output enforcement
- Experience designing LLM evals (offline + online, human-in-the-loop, synthetic data)
- Publications or open-source contributions in relevant areas
- Experience applying latest context/harness engineering techniques to customer facing products
- Founder or early-stage (first 10 engineers) or experience in standing up a new technology bet within a more established company
Benefits
- Company paid health insurance
- 401K Plan with employer match
- Self-Managed PTO
- Parental leave
- Company-provided equipment
Company Overview
Company H1B Sponsorship