Senior Manager, Intelligence Systems Lab

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In support of enterprise AI strategy, the Senior Manager of Intelligence Systems Lab conducts research into the principles of intelligence and develops agentic AI systems grounded in rigorous evaluation science. This hands‑on technical role focuses on understanding and implementing reasoning, planning, memory, and generalization capabilities for AI agents, while building benchmarking methodologies to assess agent performance. The position supports cross‑functional stakeholders in Commercial, Manufacturing, Clinical Development, and Research functions.

• Research and Framework Development

  • Conduct research on reasoning, planning, memory, and generalization architectures for AI agents and multi‑agent systems.

  • Develop and test frameworks for agent cognition, including abstraction, goal decomposition, and adaptive planning.

  • Contribute to the lab's understanding of foundational principles underlying intelligent behavior in artificial systems.

  • Stay current with academic literature and industry advances in AI reasoning, cognitive architectures, and agent design.

• Benchmarking and Evaluation Science

  • Design and execute benchmarking experiments to evaluate agent reasoning, reliability, and generalization capabilities.

  • Develop evaluation methodologies for assessing AI agent performance across diverse tasks and domains.

  • Build test harnesses, evaluation datasets, and measurement frameworks for multi‑agent systems.

  • Apply rigorous experimental design and statistical analysis to benchmark results.

• Agentic AI Development

  • Serve as a hands‑on AI engineer, designing, developing, and deploying advanced agentic solutions.

  • Build multi‑agent AI systems using frameworks such as Strands, Lang Graph, DSPy, and similar agentic architectures.

  • Develop RAG (Retrieval Augmented Generation) applications, knowledge graphs, and conversational AI solutions.

  • Implement autonomous workflows that demonstrate advances in reasoning and planning capabilities.

• Rapid Prototyping and Innovation

  • Turn research concepts into working prototypes that demonstrate advances in agent intelligence.

  • Conduct proof‑of‑concept development to assess feasibility of new reasoning and planning approaches.

  • Seek opportunities to translate research findings into production‑ready capabilities.

  • Contribute to documenting research findings, experimental results, and technical methodologies.

• Cross‑Functional Collaboration

  • Work cross‑functionally with analytics and business stakeholders to pilot AI solutions grounded in research insights.

  • Translate complex AI research concepts into business language to drive understanding and adoption.

  • Partner with the broader Applied Intelligence organization to advance agentic AI capabilities.

  • Engage with Commercial, GPS/Manufacturing, Clinical Development, and Research teams in presenting research‑informed solutions.

• Mentorship and Best Practices

  • Contribute to implementing best practices in agent evaluation, benchmarking science, and research methodology.

  • Provide guidance to junior team members on AI/ML techniques, research methods, and development approaches.

  • Support knowledge sharing through internal presentations, documentation, and collaborative research.

• Educational Background BA/BS required…