Manager, AI Engineering

Please note that this position can be based in San Diego, CA, San Francisco, CA or Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.

Position Summary

Primary Responsibilities

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  Design, develop, validate, and deploy machine learning, statistical, and GenAI solutions that address complex business problems and support enterprise priorities
  
  


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  Contribute to execution of the enterprise AI strategy and roadmap by providing technical input on use‑case feasibility, value hypotheses, architecture decisions, and build‑vs‑buy assessments
  
  


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  Build and maintain scalable ML and LLM pipelines from data ingestion through production, adhering to established ML Ops and LLM Ops standards including versioning, evaluation, observability, and rollback
  
  


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  Partner with business, analytics, IT, and security teams to identify, prototype, and deliver high‑value AI use cases across the organization
  
  


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  Evaluate and integrate AI and GenAI platform components such as model endpoints, vector databases, agent frameworks, and guardrails in alignment with enterprise architecture standards
  
  


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  Contribute to AI governance by supporting model documentation, lineage, risk assessment, bias testing, explainability, and compliance with applicable regulations and frameworks
  
  


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  Provide technical input into AI platform and vendor evaluations, including RFI/RFP activities and assessments of cost, security, and data residency
  
  


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  Support AI enablement efforts through development of reusable patterns, reference implementations, and technical documentation to accelerate adoption
  
  


• Apply and uphold policies for AI lifecycle management, bias/robustness testing, explainability, human oversight, and incident response. Support mapping of AI controls to major frameworks and regulations (e.g., NIST AI RMF, EU AI Act readiness) to ensure responsible and compliant AI deployment.


• Ensure all data science work complies with global AI regulations, ethical standards, and applicable GxP processes.


• Participate in cross-functional AI Governance Council activities as requested, providing technical expertise on model risk and data science practices.


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  Other duties as assigned
  
  

Education/Experience/Skills

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  Master’s degree or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative discipline, or equivalent practical experience
  
  


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  5+ years of hands‑on experience in applied data science and machine learning, including model development, deployment, and production support
  
  


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  Advanced proficiency in Python and common ML frameworks and tools such as scikit‑learn, TensorFlow, PyTorch, and SQL
  
  


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  Practical experience with ML Ops and LLM Ops practices including model registries, version control, evaluation benchmarks, and monitoring
  
  


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  Experience working with large language models, GenAI technologies, vector databases, or agent frameworks
  
  


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  Experience operating in a regulated environment and following GxP or similar compliance processes
  
  


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  Willingness and ability to travel domestically and internationally
  
  

Physical Requirements

This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds.  This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.

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