✦ Luna Orbit — AI & Machine Learning

Associate Director, Engineering Lead, Clinical Engineering & Operations

at Bristol-Myers Squibb

📍 Princeton - NJ - US Hybrid 💰 $171K – $207K USD / year Posted March 13, 2026
Salary $171K – $207K USD / year
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role involves leading the development of AI-native products supporting global development operations, focusing on generative AI, agentic workflows, and scalable AI platforms.

  • Develop AI strategy
  • Design AI products
  • Implement AI workflows
  • Ensure security and compliance
  • Collaborate with stakeholders

The environment requires expertise in AI frameworks, fullstack engineering, model selection, CI/CD practices, and security/compliance standards for AI solutions.

The ideal candidate is a senior AI engineer with hands-on experience in developing generative and agentic AI solutions, fullstack engineering expertise, and a strategic mindset for AI product development in a regulated environment.

AIArtificial IntelligenceGenerative AIFullstack EngineeringModel SelectionAI Product Development
Agentic WorkflowsData-driven IntelligenceSecurity & Compliance
AI FrameworksCI/CD ToolsSecurity & Compliance Tools
AIArtificial IntelligenceGenerative AIAgentic WorkflowsData-driven IntelligenceFullstack EngineeringModel SelectionAI Product DevelopmentCI/CDSecurity & Compliance
AIArtificial IntelligenceGenerative AIAgentic WorkflowsData-driven IntelligenceFullstack EngineeringMachine LearningModel SelectionAI Product DevelopmentCI/CDSecurity & Compliance
LeadershipCollaborationProblem-solvingStrategic ThinkingCommunication
Industry Pharmaceuticals & Biotechnology
Job Function AI product leadership supporting clinical development operations
AIArtificial IntelligenceGenerative AIAgentic WorkflowsData-driven IntelligenceFullstack EngineeringModel SelectionAI ProductCI/CDSecurity & ComplianceAI Product Development

Lack of experience with AI and machine learning, No experience in regulated environments, Inability to work in a hybrid setting

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