Associate Director, AI/ML Engineering

<div class="content-intro"><p></p> <div data-ogsc="black"><span data-ogsc="" data-ogsb="yellow"><strong data-ogsc="" data-olk-copy-source="MessageBody">About Acadia Pharmaceuticals</strong></span></div> <div data-ogsc="black">&nbsp;</div> <div data-ogsc="black"><span data-ogsc="" data-ogsb="yellow">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.</span></div></div><h3>Please note that this position is based in San Diego, CA, South San Francisco, CA, or Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.</h3> <p><strong><u>Position Summary</u></strong></p> <div> <div>The Associate Director, AI/ML Engineering serves as a hands-on technical leader driving the design, architecture, and delivery of Generative AI and agentic AI solutions across the enterprise. This role builds scalable multi-agent systems, connects AI solutions to enterprise data and tools, and ensures safe, reliable deployment through robust evaluation and guardrail frameworks. The position also applies strong machine learning and foundation model expertise to deliver high-impact use cases within a regulated biopharmaceutical environment.</div> </div> <p><strong><u>Primary Responsibilities</u></strong></p> <ul> <li> <p>Design, build, and deploy agentic AI workflows that automate and transform complex business processes, leveraging multi-agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or equivalent).</p> </li> <li> <p>Architect and implement MCP servers to expose enterprise tools, APIs, and data sources as standardized capabilities consumable by AI agents.</p> </li> <li> <p>Connect multi-agent systems to enterprise databases, internal APIs, and MCP servers to enable grounded, context-aware, and action-oriented AI solutions.</p> </li> <li> <p>Partner cross-functionally with internal teams to define data contracts, lineage standards, and quality thresholds required for AI/ML use cases.</p> </li> <li> <p>Design and im