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Staff Applied AI Researcher - Agentic Reasoning Systems (Brazil)

Articul8· Applied Research
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Dublin, CA (HQ)Full-timePosted 5mo ago

About the role

Staff-level applied AI researcher focusing on runtime decisioning and trustworthy autonomous systems within Articul8’s ModelMesh-based platform. Leads research on agentic reasoning, orchestration, evaluation, and production-grade reliability for enterprise-grade autonomous AI.

Responsibilities

  • Set technical direction for agentic reasoning systems and runtime intelligence across ModelMesh™ — define orchestration strategies, decision policies, verification approaches, and runtime quality standards that govern massively parallel agent systems in production
  • Architect the infrastructure for researcher augmentation at scale — design agentic platforms and orchestration primitives to deploy fleets of AI agents for experimentation, evaluation, and production integration
  • Go deep: advance the science of autonomous reasoning — design, train, and refine learned components behind runtime decisioning (routing models, verification models, confidence estimators, reward models, policy selectors)
  • Go broad: unify perception, retrieval, reasoning, and action — create repeatable methodology for composing domain-specific models, data perception systems, knowledge graphs, retrieval layers, and external tools into coherent agentic workflows
  • Drive research on agent reliability for regulated environments — lead failure detection, self-checking, verification workflows, and auditable autonomous behavior research at scale
  • Define evaluation methodology for runtime intelligence — establish metrics for task success, decision quality, robustness, traceability, and failure recovery; build continuous evaluation harnesses
  • Influence platform-level architecture — shape model routing, tool use, observability, governance, access control, and interoperability with external agent ecosystems
  • Mentor researchers across levels in the agentic paradigm — raise technical judgment, experimental rigor, and agent-augmented research practices
  • Maintain hands-on research impact — contribute through publications, patents, and externally visible output to model deep technical leadership

Qualifications

  • PhD or MSc in Computer Science, Machine Learning, AI, Robotics, or a related field.
  • 8+ years in AI/ML research with impact on production systems, including 3+ years building LLM-based or autonomous AI systems.
  • Deep hands-on experience in at least two of: multi-agent coordination, planning under uncertainty, sequential decision-making, probabilistic inference, model routing, or tool-using agent systems.
  • Experience designing evaluation frameworks for autonomous systems in production-like conditions.
  • Experience designing and operating research systems that integrate multiple models, data sources, and control mechanisms in production or near-production settings.
  • Proficient in Python with strong software architecture instincts.
  • Technical leadership: experience setting technical direction and mentoring researchers.

Skills

Required:Multi-agent coordinationPlanning under uncertaintySequential decision-makingModel routing
Nice to have:Probabilistic inference

Benefits

  • Not specified in the description
Last updated Aug 5, 2026. Interested? Apply on the company site.
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