Associate Director, Intelligence Systems Lab

Working with Us

Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it.

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This role leads research into the principles of intelligence and architects advanced agentic AI systems grounded in rigorous evaluation science. The Associate Director is responsible for advancing the lab's understanding of reasoning, planning, memory, and generalization in AI agents, while establishing benchmarking methodologies that set the standard for agent evaluation. This position is pivotal in shaping the strategic direction of intelligence systems research and implementing advanced frameworks that accelerate insight generation across Commercial, Manufacturing, Clinical Development, and Research functions.

• Research Leadership and Framework Architecture
  • Lead research initiatives exploring foundational principles of intelligence, including reasoning, planning, memory, and generalization in AI systems.
  • 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 in artificial systems.
  • Synthesize academic literature and industry advances to shape the lab's technical roadmap for reasoning and cognitive architectures.
  • Publish findings and represent the lab's research at internal forums and external conferences.
• Benchmarking and Evaluation Science Leadership
  • Lead the development of benchmarking and evaluation science for AI agents, establishing rigorous methodologies to assess reasoning, planning, and generalization.
  • 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 the design and development of multi-agent AI systems using frameworks such as Strands, Lang Graph, DSPy, and similar agentic architectures.
  • Oversee development of RAG applications, knowledge graphs, and conversational AI solutions informed by research insights.
  • Drive the implementation of autonomous workflows and decision systems that demonstrate 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 and business stakeholders across Commercial, GPS/Manufacturing, Clinical Development, and Research functions to translate research into business value.
  • Collaborate with IT, data engineering, and platform teams to ensure research prototypes are deployable on enterprise infrastructure.
  • Translate complex AI research insights into actionable…