Associate Director, Intelligence Systems Lab

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This Associate Director leads research into the principles of intelligence and designs advanced agentic AI systems grounded in rigorous evaluation science. The role advances the lab’s understanding of reasoning, planning, memory, and generalization in AI agents and establishes benchmarking methodologies that set the standard for agent evaluation across Commercial, Manufacturing, Clinical Development, and Research functions.

• Research Leadership and Framework Architecture
  • Lead initiatives exploring foundational principles of intelligence (reasoning, planning, memory, generalization).
  • Architect frameworks for agent cognition, abstraction, goal decomposition, and adaptive planning; establish design principles for multi‑agent systems.
  • Define research hypotheses and experimental agendas that advance the lab’s understanding of intelligent behavior.
  • Synthesize academic literature and industry advances to shape the technical roadmap.
  • Publish findings and represent the lab at internal forums and external conferences.
• Benchmarking and Evaluation Science Leadership
  • Develop benchmark and evaluation science for AI agents, establishing rigorous methodologies.
  • Define evaluation frameworks and success criteria for multi‑agent systems across diverse enterprise use cases.
  • Oversee the creation of test harnesses, evaluation datasets, and measurement standards.
  • Ensure experimental rigor and reproducibility across all benchmarking activities.
  • Set the strategic direction for how the organization measures and validates agent intelligence.
• Agentic AI Development and Implementation
  • Lead design and development of multi‑agent AI systems using frameworks such as Strands, Lang Graph, DSPy, and similar.
  • Oversee RAG applications, knowledge graphs, and conversational AI solutions informed by research insights.
  • Drive implementation of autonomous workflows and decision systems demonstrating advances in agent reasoning.
  • Ensure solutions reflect the latest research in planning, memory, and generalization capabilities.
• Rapid Prototyping and Innovation
  • Translate research concepts into working prototypes and production‑ready demonstrations.
  • Apply ROI‑first evaluation approaches to prioritize high‑impact research initiatives.
  • Identify opportunities to deploy next‑generation reasoning and planning capabilities across the enterprise.
  • Lead documentation efforts for research findings, experimental results, and technical methodologies.
• Cross‑Functional Collaboration
  • Partner with analytics, business stakeholders, IT, data engineering, and platform teams to translate research into business value.
  • Collaborate with Enterprise infrastructure teams to ensure prototypes are deployable.
  • Translate complex AI research insights into actionable recommendations for technical and non‑technical stakeholders.
  • Represent the Intelligence Systems Lab in enterprise‑wide AI initiatives and strategic planning.
• Team Development and Best Practices
  • Mentor and develop data scientists and researchers; build a culture of scientific rigor and curiosity.
  • Establish governance frameworks and best practices for agent evaluation, benchmarking science, and research methodology.
  • Lead knowledge sharing through internal presentations, publications, and collaborative initiatives.
  • Shape team capabilities and hiring strategies to advance the lab’s mission.

• Educational Background: BA/BS required in a quantitative area (Computer Science, Data Science, Statistics, Mathematics,…