Manager, AI Engineering
Acadia Pharmaceuticals
July 02, 2026
Remote friendly (Princeton, NJ)
United States
IT
Position Summary:
The Manager, AI Engineering designs, builds, and deploys scalable AI/ML and GenAI solutions delivering measurable business impact across R&D, Commercial, and Corporate, supporting enterprise AI strategy and responsible AI governance.
Primary Responsibilities:
- Design, develop, validate, and deploy ML/statistical/GenAI solutions for complex business problems.
- Support enterprise AI strategy/roadmap with technical input (use-case feasibility, value hypotheses, architecture, build-vs-buy).
- Build and maintain scalable ML and LLM pipelines (data ingestion to production) following ML Ops/LLM Ops (versioning, evaluation, observability, rollback).
- Partner with business, analytics, IT, and security to prototype and deliver high-value AI use cases.
- Evaluate/integrate AI & GenAI platform components (endpoints, vector databases, agent frameworks, guardrails) to enterprise standards.
- Support AI governance (documentation, lineage, risk assessment, bias testing, explainability, regulatory compliance).
- Provide technical input for AI platform/vendor evaluations (RFI/RFP; cost, security, data residency).
- Create reusable patterns, reference implementations, and technical documentation to accelerate adoption.
- Uphold AI lifecycle management policies (bias/robustness, explainability, human oversight, incident response) and map controls to major frameworks.
Education/Experience/Skills:
- Master’s or PhD in Data Science/Statistics/CS/Math (or equivalent).
- 5+ years applied ML/data science (model development, deployment, production support).
- Advanced Python; scikit-learn, TensorFlow, PyTorch, SQL.
- ML Ops/LLM Ops experience (registries, version control, evaluation, monitoring).
- Experience with LLMs/GenAI, vector databases, or agent frameworks.
- Regulated environment + GxP/compliance experience.
- Travel domestically/internationally.
Benefits (US-based employees):
Medical/dental/vision; employer-paid life/disability/travel/EAP; 401(k) match; ESPP; 15+ vacation days; paid holidays; paid sick time; paid parental leave; tuition assistance.
The Manager, AI Engineering designs, builds, and deploys scalable AI/ML and GenAI solutions delivering measurable business impact across R&D, Commercial, and Corporate, supporting enterprise AI strategy and responsible AI governance.
Primary Responsibilities:
- Design, develop, validate, and deploy ML/statistical/GenAI solutions for complex business problems.
- Support enterprise AI strategy/roadmap with technical input (use-case feasibility, value hypotheses, architecture, build-vs-buy).
- Build and maintain scalable ML and LLM pipelines (data ingestion to production) following ML Ops/LLM Ops (versioning, evaluation, observability, rollback).
- Partner with business, analytics, IT, and security to prototype and deliver high-value AI use cases.
- Evaluate/integrate AI & GenAI platform components (endpoints, vector databases, agent frameworks, guardrails) to enterprise standards.
- Support AI governance (documentation, lineage, risk assessment, bias testing, explainability, regulatory compliance).
- Provide technical input for AI platform/vendor evaluations (RFI/RFP; cost, security, data residency).
- Create reusable patterns, reference implementations, and technical documentation to accelerate adoption.
- Uphold AI lifecycle management policies (bias/robustness, explainability, human oversight, incident response) and map controls to major frameworks.
Education/Experience/Skills:
- Master’s or PhD in Data Science/Statistics/CS/Math (or equivalent).
- 5+ years applied ML/data science (model development, deployment, production support).
- Advanced Python; scikit-learn, TensorFlow, PyTorch, SQL.
- ML Ops/LLM Ops experience (registries, version control, evaluation, monitoring).
- Experience with LLMs/GenAI, vector databases, or agent frameworks.
- Regulated environment + GxP/compliance experience.
- Travel domestically/internationally.
Benefits (US-based employees):
Medical/dental/vision; employer-paid life/disability/travel/EAP; 401(k) match; ESPP; 15+ vacation days; paid holidays; paid sick time; paid parental leave; tuition assistance.