About Acadia Pharmaceuticals Acadia is committed to turning scientific promise into meaningful innovation that makes the difference for underserved neurological and rare disease communities around the world. Our commercial portfolio includes the first and only FDA-approved treatments for Parkinson’s disease psychosis and Rett syndrome. We are developing the next wave of therapeutic advancements with a robust and diverse pipeline that includes mid- to late-stage programs in Alzheimer’s disease psychosis and Lewy body dementia psychosis, along with earlier-stage programs that address other underserved patient needs.

At Acadia, we’re here to be their difference. 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 The Manager, AI Engineering plays a key role in advancing Acadia’s enterprise AI and analytics capabilities. This role designs, builds, and deploys scalable AI/ML and GenAI solutions that deliver measurable business impact across R&D, Commercial, and Corporate functions. As a core member of the Artificial Intelligence organization, the Manager will contribute to the enterprise AI strategy, support responsible AI governance, and help operationalize advanced analytics and machine learning at scale across Acadia globally.

Responsibilities

Design, develop, validate, and deploy machine learning, statistical, and GenAI solutions that address complex business problems and support enterprise priorities 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 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 Partner with business, analytics, IT, and security teams to identify, prototype, and deliver high‑value AI use cases across the organization Evaluate and integrate AI and GenAI platform components such as model endpoints, vector databases, agent frameworks, and guardrails in alignment with enterprise architecture standards Contribute to AI governance by supporting model documentation, lineage, risk assessment, bias testing, explainability, and compliance with applicable regulations and frameworks Provide technical input into AI platform and vendor evaluations, including RFI/RFP activities and assessments of cost, security, and data residency 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. , 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.