Head of Data/AI Infrastructure

Cloud Platform | Technology Division

Chubb is a leading underwriting company. We assess, assume, and manage risk with insight and discipline. Chubb has embarked on a transformation journey to enhance our underwriting capabilities and develop into a leading Underwriting Engineering and Data Analytics company. Cloud Platform is a key enabler of this digital transformation, and Data and Artificial Intelligence are at the heart of Chubb's next phase of growth.

As such, we are seeking a visionary and experienced Head of Data/AI Engineering to lead the design, development, and delivery of enterprise-wide data and AI/ML platforms on cloud. The successful candidate will drive Chubb's data and AI strategy, building scalable data infrastructure, advanced analytics capabilities, and machine learning platforms that transform how Chubb underwrites risk and serves its customers.

The Head of Data/AI Engineering will serve as a senior technical leader and strategic partner to business stakeholders, working across the organization to deliver AI-powered solutions that are secure, governed, and production-ready. This is a unique opportunity for the right leader to shape and build Chubb's data and AI engineering capabilities from the ground up on cloud.

Responsibilities

• Provide executive leadership for Chubb's Data and AI Infrastructure strategy. Define and own the roadmap for enterprise data platforms, AI/ML infrastructure, and advanced analytics capabilities on cloud (Azure/GCP).
• Lead and grow a high-performing team of Cloud data engineers, and AI architects. Foster a culture of innovation, engineering excellence, and continuous learning.
• Partner with business stakeholders, underwriting teams, and product owners to identify AI/ML opportunities and translate them into scalable, production-grade engineering solutions.
• Architect and oversee the build of enterprise data platforms including data lakes, data warehouses, real-time streaming pipelines, and feature stores on cloud.
• Drive the design and deployment of ML/AI platforms (MLOps) to support model development, training, versioning, monitoring, and production serving at scale.
• Define and enforce data governance, data quality, lineage, and security standards in collaboration with enterprise architecture and security teams.
• Lead adoption of generative AI and LLM capabilities, evaluating emerging frameworks and tools to identify practical business applications within Chubb's operating environment.
• Collaborate with the broader Cloud Platform team and Data Analytics teams to ensure data and AI workloads adhere to Chubb's Cloud Adoption Framework, security standards, and cost management practices.
• Implement CI/CD and automation pipelines for data and AI workflows, ensuring reliable and repeatable delivery of data products and models.
• Present roadmap progress, platform capabilities, and strategic recommendations to senior stakeholders and executives; represent the Data/AI Engineering function in key forums.
• Manage vendor relationships and evaluate third-party AI/data tools and services to accelerate capability delivery and reduce build vs. buy costs.
• Drive cost optimization of data and AI infrastructure, implementing right-sized compute, storage, and licensing strategies on cloud.

• Bachelor's degree in Computer Science, Data Engineering, Mathematics, or a relevant field. Advanced degree (Master's or PhD) in a quantitative discipline preferred.
• Minimum 15 years of experience in data and technology roles, with at least 5 years in a senior engineering leadership position overseeing Data and AI/ML platforms.
• Proven experience architecting and delivering large-scale data platforms on cloud (Azure and/or GCP strongly preferred), including data lakes, lakehouses, and streaming platforms.
• Deep expertise in ML/AI engineering and MLOps practices — including model lifecycle management, feature engineering, experiment tracking, and model serving (e.g., Vertex AI, Azure ML, MLflow, Kubeflow).
• Strong hands-on experience with big data and data engineering technologies such as Apache Spark, Databricks, dbt, Apache Kafka, and cloud-native equivalents (BigQuery, Synapse, Dataflow).
• Experience with Generative AI and Large Language Models (LLMs), including prompt engineering, fine-tuning, RAG architectures, and responsible AI practices.
• Solid understanding of Infrastructure as Code (Terraform, Ansible) and CI/CD pipelines (Jenkins, GitHub Actions) applied to data and AI workloads.
• Experience with data governance frameworks, data cataloguing, and tools such as Collibra, Purview, or Dataplex.
• Relevant cloud and/or data certifications (e.g., Google Professional Data Engineer, Azure Data Engineer Associate, GCP Professional ML Engineer).
• Proven ability to lead cross-functional teams and manage stakeholders at executive level; exceptional communication and influencing skills.
• Experience in regulated industries (financial services, insurance) with working knowledge of data privacy regulations (GDPR, CCPA) is a strong advantage.

If you are a strategic thinker and hands-on engineering leader with a passion for building world-class Data and AI platforms, we encourage you to apply. The successful candidate will play a pivotal role in shaping how Chubb harnesses data and artificial intelligence to lead the future of insurance underwriting.

The pay range for the role is $200,00 to $280,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.