Senior Manager, AI Engineering
Acadia Pharmaceuticals
August 13, 2026
Remote friendly (South San Francisco, CA)
United States
IT
Position Summary
Senior Manager, AI Engineering—advance Acadia’s enterprise AI capabilities through development, deployment, governance of scalable AI/ML solutions. Partner with R&D, Commercial, and Corporate stakeholders to translate data into actionable insights and business value.
Primary Responsibilities
- Execute enterprise AI strategy/roadmap; align AI/ML initiatives to business priorities; identify high-value use cases
- Develop and deliver AI/ML solutions and analytics/data science use cases supporting data-driven decisions
- Provide technical expertise for AI governance (model risk, responsible AI, lifecycle management)
- Assess feasibility, business value, and implementation risks to support prioritization/investment decisions
- Design, develop, validate, deploy, and support ML models and scalable ML/LLM pipelines using ML Ops/LLM Ops
- Evaluate/optimize GenAI (LLMs, vector databases, endpoints, agent frameworks, guardrails) per enterprise architecture
- Maintain documentation (model/prompt/dataset) for lineage, auditability, approvals, and system-of-record compliance
- Create reusable frameworks/standards to accelerate adoption, scalability, and operational efficiency
- Partner with IT, Data Insights & Analytics, and Information Security on platforms, infrastructure, vendor/RFI/RFP
- Apply responsible AI standards (bias/robustness, explainability, human oversight, incident response, regulatory compliance)
- Support GxP and evolving AI regulation alignment (e.g., NIST AI RMF, EU AI Act readiness)
Education/Experience/Skills
- MS in a quantitative field with 5+ years experience, or PhD with 2+ years industry (or equivalent research) in ML/AI/data science
- Experience deploying/supporting ML/AI in production or research
- Proficiency in Python, SQL; PyTorch/TensorFlow/scikit-learn
- GenAI experience (LLMs, RAG, vector databases, agent frameworks)
- ML Ops/LLM Ops (version control, evaluation, monitoring, deployment)
- Knowledge of responsible AI, explainability, evaluation, and AI governance; regulated environments preferred
- Domestic/international travel as needed
Benefits
- Discretionary bonus and equity awards; $150,300—$187,900 salary range
- Medical/dental/vision; employer-paid life/disability/business travel/EAP; 401(k) match 1:1 up to 5%; Employee Stock Purchase Plan; 15+ vacation days; 13–15 paid holidays; paid sick time; paid parental leave; tuition assistance
Senior Manager, AI Engineering—advance Acadia’s enterprise AI capabilities through development, deployment, governance of scalable AI/ML solutions. Partner with R&D, Commercial, and Corporate stakeholders to translate data into actionable insights and business value.
Primary Responsibilities
- Execute enterprise AI strategy/roadmap; align AI/ML initiatives to business priorities; identify high-value use cases
- Develop and deliver AI/ML solutions and analytics/data science use cases supporting data-driven decisions
- Provide technical expertise for AI governance (model risk, responsible AI, lifecycle management)
- Assess feasibility, business value, and implementation risks to support prioritization/investment decisions
- Design, develop, validate, deploy, and support ML models and scalable ML/LLM pipelines using ML Ops/LLM Ops
- Evaluate/optimize GenAI (LLMs, vector databases, endpoints, agent frameworks, guardrails) per enterprise architecture
- Maintain documentation (model/prompt/dataset) for lineage, auditability, approvals, and system-of-record compliance
- Create reusable frameworks/standards to accelerate adoption, scalability, and operational efficiency
- Partner with IT, Data Insights & Analytics, and Information Security on platforms, infrastructure, vendor/RFI/RFP
- Apply responsible AI standards (bias/robustness, explainability, human oversight, incident response, regulatory compliance)
- Support GxP and evolving AI regulation alignment (e.g., NIST AI RMF, EU AI Act readiness)
Education/Experience/Skills
- MS in a quantitative field with 5+ years experience, or PhD with 2+ years industry (or equivalent research) in ML/AI/data science
- Experience deploying/supporting ML/AI in production or research
- Proficiency in Python, SQL; PyTorch/TensorFlow/scikit-learn
- GenAI experience (LLMs, RAG, vector databases, agent frameworks)
- ML Ops/LLM Ops (version control, evaluation, monitoring, deployment)
- Knowledge of responsible AI, explainability, evaluation, and AI governance; regulated environments preferred
- Domestic/international travel as needed
Benefits
- Discretionary bonus and equity awards; $150,300—$187,900 salary range
- Medical/dental/vision; employer-paid life/disability/business travel/EAP; 401(k) match 1:1 up to 5%; Employee Stock Purchase Plan; 15+ vacation days; 13–15 paid holidays; paid sick time; paid parental leave; tuition assistance