This role pays less than
87%
of similar roles. Most pay
$169,550–$258,000
— the shaded band above.
At the midpoint, this role pays about
$157k
versus about
$214k
for comparable roles.
Based on 240 similar postings.
Employer
About Neurocrine
Neurocrine Biosciences is a biopharmaceutical company focused on discovering and developing treatments for neurological and endocrine-related conditions, including tardive dyskinesia, Parkinson''s disease, and endometriosis. Industry: Biopharmaceuticals & Neuroscience
Neurocrine currently has
6 open roles
on FindRole.
Listed pay typically runs
$132,700–$182,000
across 6 roles with salary data.
Principal, Enterprise AI Platform & Strategy leads enterprise-wide initiatives to define, deliver, and mature core AI and machine learning platforms. This role combines technical program leadership, platform product management, and strategic advisory to accelerate the adoption of secure, scalable, and governed AI capabilities. The individual will own the strategy and roadmap for components including model orchestration, RAG pipelines, embedding services, prompt governance, vector search, and performance monitoring. They will evaluate foundation models and third-party services while ensuring alignment with Responsible AI principles. Key technical requirements include experience with LLM orchestration, vector databases, telemetry, and observability. The role addresses the challenge of integrating advanced analytics and automation into a regulated pharmaceutical environment by establishing governance frameworks, managing multi-team execution via Agile methodologies, and translating complex business needs into actionable technical roadmaps to ensure long-term platform sustainability and value.
Own the strategy, roadmap, and lifecycle for enterprise AI/ML platforms including RAG pipelines and model orchestration.
Evaluate and integrate foundation models, third-party AI services, and emerging technologies into the corporate infrastructure.
Serve as the primary technical expert to advise leadership on AI feasibility, solution patterns, and architectural alignment.
Develop and manage the Responsible AI governance framework in coordination with Legal, Cybersecurity, and Compliance teams.
Lead the end-to-end execution of multi-team programs using Agile/Scrum methodologies to deliver scalable platform capabilities.
Establish and monitor performance metrics such as accuracy, latency, and cost optimization for all AI services.
Translate ambiguous business requirements into actionable technical roadmaps and measurable KPIs for executive reporting.
What we're looking for
Bachelor’s degree in Computer Science, Information Technology, or a related field, or an equivalent combination of education and experience.
PMP certification (or in progress) is preferred.
10+ years of relevant experience in IT or related disciplines, ideally within the pharmaceutical industry or a similar regulated environment.
Working knowledge of enterprise AI components including RAG pipelines, embedding services, LLM orchestration, prompt governance, and model performance monitoring.
Understanding of foundation models, vector databases, third-party AI services, and AI safety/responsible AI concepts.
Experience delivering automation frameworks, integration platforms, reusable services, and managing platform reliability through telemetry and SLOs.
Familiarity with data privacy, security requirements, governance frameworks, and API lifecycle management.
Proven ability to drive complex multi-team initiatives using Agile/Scrum methodologies and translate business needs into technical roadmaps.
Python
Go
Java
C++
Kubernetes
OCI
LLM
Machine Learning
PyTorch
TensorFlow
Hugging Face
CI/CD
Microservices
Distributed Systems
Infrastructure Automation
Google Cloud
Vertex AI
BigQuery
GKE
Terraform
Kubernetes
GitOps
Pub/Sub
Dataflow
Cloud Run
OpenTelemetry
Microservices
Distributed Systems
DevSecOps
Retrieval-Augmented Generation
Service Mesh
AI Infrastructure
MLOps
Generative AI
Agentic AI
GPU
CPU
High Performance Storage
Networking
Private Cloud
Data Center Design
Predictive ML
RFI
RFP
Scalable Platforms
AI
LLM Gateways
machine-learning
APIs
Distributed Systems
Telemetry
Observability
Kong
MCP
Prompt Management
Model Lifecycle Management
Red Teaming
Drift Detection
FinOps
Identity and Authorization
Data Architecture
A2A