Director, Group Head (AI Systems & Scale)

Novartis

Hybrid

Quick summary

Work type: Hybrid
Location: Cambridge
Salary: $194,600–$361,400 / yr
Posted: 3 days ago
Closes: Jun 17, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $227k

This role $278k

$175k most similar roles pay here $381k

This role pays more than 85% of similar roles. Most pay $202,662–$251,750 — the shaded band above. At the midpoint, this role pays about $278k versus about $227k 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 8 open roles on FindRole.

Listed pay typically runs $194,600–$361,400 across 8 roles with salary data.

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View all roles at Novartis

At a glance

TL;DR · Director, Group Head (AI Systems & Scale)

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As Director & Group Head of AI Systems & Scale at Novartis’s AI4R team in Cambridge, USA, you will lead the development and deployment of advanced AI systems to accelerate drug discovery. Your role involves defining a multi-year roadmap for scalable AI platforms, leading multidisciplinary teams to build production-grade solutions, and establishing reference architectures for agentic systems. You will ensure robust governance and compliance while driving cross-functional collaboration to prioritize high-impact initiatives. Essential skills include extensive experience in machine learning across drug discovery domains, proficiency in Python and deep learning frameworks, and the ability to explain complex concepts clearly. Ideal candidates also have expertise in enterprise-scale agentic platforms and large model training in cloud environments. This role focuses on leveraging AI to enhance biomedical research efficiency and speed up therapeutic development for patient benefit.

Skills

Python TensorFlow Keras PyTorch AWS Azure Google Cloud Platform Docker Kubernetes CI/CD Git PostgreSQL MongoDB Agile Machine Learning Deep Learning NLP Time Series Analysis Statistical Analysis Data Governance

What you'll do

Define and lead the multi-year roadmap for scalable AI systems across research.
Lead multidisciplinary teams to deliver production-grade AI systems and intelligent applications.
Establish reference architectures for agentic systems with orchestration and memory components.
Build enterprise agentic platforms with reusable workflows and evaluation frameworks.
Own agent quality engineering, including policy enforcement and failure detection mechanisms.
Drive scalable deployment strategies ensuring performance, reliability, and cost efficiency.
Define performance metrics linking AI system effectiveness to scientific outcomes.

What we're looking for

Demonstrated experience leading machine learning initiatives across multiple drug discovery domains.
Strong background in applying machine learning to computational chemistry or protein modeling.
Expertise in large model training and deployment using high-performance computing environments.
Deep understanding of biomedical sciences and therapeutic discovery.
Proficient coding skills in Python with deep learning frameworks and version control systems.
Proven ability to manage complexity, align stakeholders, and deliver results in matrixed environments.
Experience building enterprise-scale agentic platforms including orchestration and memory systems.

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