Senior Manager, AI Engineering

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

Position Summary

Primary Responsibilities

• Contribute to the execution of the enterprise AI strategy and roadmap by aligning AI and machine learning initiatives with business priorities and identifying high-value use cases across the organization
• Partner with stakeholders across R&D Commercial and Corporate Functions to identify and develop AI and machine learning solutions that drive business value
• Deliver analytics and data science use cases that generate actionable insights and support data-driven decision-making
• Support cross-functional AI governance activities by providing technical expertise on model risk responsible AI practices and lifecycle management
• Assess the technical feasibility business value and implementation risks of proposed AI and data science initiatives to support prioritization and investment decisions
• Design develop validate deploy and support machine learning models statistical analyses and scalable ML/LLM pipelines using established ML Ops and LLM Ops practices
• Evaluate implement and optimize GenAI technologies including large language models vector databases model endpoints agent frameworks and guardrail solutions aligned with enterprise architecture standards
• Maintain model prompt and dataset documentation ensuring lineage auditability governance compliance approvals and adherence to enterprise AI system-of-record standards
• Develop reusable data science frameworks reference implementations and technical standards that accelerate AI adoption scalability and operational efficiency across the enterprise
• Partner with Information Technology Data Insights & Analytics and Information Security teams to support AI platforms infrastructure capabilities technology selection vendor assessments and RFI/RFP evaluations
• Apply AI governance and responsible AI standards including model lifecycle management bias and robustness testing explainability human oversight incident response and regulatory compliance requirements
• Support compliance with applicable GxP requirements and evolving AI regulations including alignment with frameworks such as NIST AI RMF and EU AI Act readiness standards
• Contribute to AI enablement initiatives through knowledge sharing technical documentation practitioner education portfolio reviews and cross-functional collaboration that promotes responsible AI adoption
• Monitor emerging AI machine learning and regulatory developments to inform solution design platform evolution and enterprise AI capabilities
• Provide technical recommendations on AI solution architecture platform strategy and build-versus-buy decisions
• Other duties as assigned

Education/Experience/Skills

• Masters degree in Data Science Statistics Computer Science Mathematics Engineering or a related quantitative discipline with 5 years of relevant experience; OR PhD in a related quantitative discipline with 2 years of industry experience or equivalent advanced research experience in machine learning artificial intelligence or data science
• Experience developing deploying and supporting machine learning and AI solutions in production or research environments
• Proficiency in Python SQL and AI/ML frameworks such as PyTorch TensorFlow or scikit-learn
• Experience working with Generative AI technologies large language models retrieval-augmented generation (RAG) vector databases and agent frameworks
• Experience with ML Ops or LLM Ops practices including version control model evaluation monitoring and deployment workflows
• Knowledge of responsible AI principles model explainability evaluation methodologies and AI governance concepts
• Experience working within regulated or compliance-focused environments preferred
• Ability to travel domestically and internationally as needed

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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