This role pays more than
92%
of similar roles. Most pay
$204,980–$278,912
— the shaded band above.
At the midpoint, this role pays about
$322k
versus about
$242k
for comparable roles.
Based on 239 similar postings.
Employer
About Novartis
Novartis is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs in areas including oncology, immunology, neuroscience, and cardiology. Industry: Biopharmaceuticals
Novartis currently has
26 open roles
on FindRole.
Listed pay typically runs
$194,600–$361,400
across 26 roles with salary data.
Executive Director, Agentic Lab and Architecture Lead leads the technical architecture, standards, and innovation roadmap for enterprise agentic AI capabilities. This role oversees the Agentic Lab to prototype, validate, and industrialize next-generation technologies while establishing reusable architectural patterns for orchestration, memory, evaluation, observability, tool use, RAG, and API integration. The position involves building proof-of-concepts, accelerators, and reference implementations to streamline development across product teams. Key responsibilities include ensuring alignment with security, Responsible AI, and data governance requirements while transitioning validated prototypes into production-ready capabilities. The role requires expertise in LLMs, agent frameworks, vector and graph databases, and cloud-native engineering. Technical tools mentioned include Microsoft Azure AI Foundry, OpenAI, Semantic Kernel, Copilot Studio, LangChain, LangGraph, and MCP/A2A protocols. The work focuses on solving the challenge of scaling secure, governed agentic AI within a regulated enterprise environment.
Define technical architecture, reference patterns, and engineering standards for enterprise agentic AI capabilities.
Establish reusable patterns for agent orchestration, memory, evaluation, tool use, RAG, and system integration.
Lead the Agentic Lab to prototype, validate, and conduct controlled incubation of new AI technologies.
Build proof-of-concepts, accelerators, and architectural blueprints to accelerate time-to-value for product teams.
Transition validated prototypes into production-ready enterprise capabilities through cross-functional partnership and documentation.
Embed Responsible AI, security, privacy, and data governance requirements into all agentic architectures.
Define evaluation and monitoring metrics for reliability, explainability, and performance of AI agents.
Coach and develop technical talent while communicating architectural decisions to senior stakeholders in executive-ready language.
What we're looking for
Bachelor's or advanced degree in Computer Science, Artificial Intelligence, Engineering, or a related technical discipline.
12+ years of experience designing enterprise software platforms, AI architectures, data/AI products, or cloud-native engineering capabilities with executive-level leadership.
Deep architecture expertise in LLMs, agent frameworks, RAG, vector/graph databases, and cloud-native deployment.
Proven ability to define enterprise reference architectures, standards, and reusable patterns for secure, scalable, and governed agentic AI.
Hands-on experience with modern software engineering practices including CI/CD, testing, telemetry, and cost/performance optimization.
Strong fluency in Responsible AI, security, privacy, data governance, and compliance requirements for regulated enterprise environments.
Experience building agentic AI platforms or architecture practices in pharma, healthcare, life sciences, or financial services (preferred).
Familiarity with Microsoft Azure AI Foundry, Semantic Kernel, Copilot Studio, LangChain/LangGraph, and other relevant AI tools (preferred).
LLMs
Agent Frameworks
RAG
Vector Databases
Python
Prompt Engineering
Machine Learning
Deep Learning
Cloud-native Development
APIs
Data Science
Statistical Analysis
Time Series Analysis
Data Visualization
Observability