Document ingestion is a top priority for Chubb and we are looking for an innovative, results-oriented Principal Engineering Architect with requisite experience and ambition to drive the end to end hybrid cloud based architecture and engineering of the Document Ingestion program. 

We are looking for a passionate, dynamic and business focused Principal Document AI & Engineering Architect to join our Document AI and Engineering leadership team. The candidate should have a strong technical background in cloud platforms and cloud data domains, have exceptional organizational skills, written and verbal communication skills and be an exceptionally analytical and structured thinker. 

The successful candidate would bring a demonstrable track record of successfully developing cloud architecture frameworks, designs, and delivering modern cloud data platform solutions to help drive Document AI data engineering practice growth. 

We are looking for candidates who have demonstrated excellence in helping data engineering teams in their cloud data engineering journey, developing roadmaps and blueprints for cloud data engineering adoption, and leading a team of technical cloud architects. The successful candidate must be a hands-on person with proven ability to engage in innovative technology environments that embrace machine learning and AI as well as public cloud, open-source technologies and agile environments for document classification, ingestion, enrichment workflows. 

The successful candidate should have superb data engineering, cloud architecture, business and communication skills to be able to work with functional leaders to define and prioritize key data design authority principles, design & viable data products with a hybrid cloud platform.

Requirements

The Principal Document AI & Engineering Architect must have a demonstrated track record of delivering results in a matrixed environment with a focus on Data Engineering and architecture. Given Chubb’s global presence, the individual must also possess strong collaboration, partnership, and negotiation skills with an orientation towards driving tangible business results. This individual must also serve as a change agent and drive the engineering process of modernizing our document ingestion workflows to meet the emerging needs of the Company.

• Lead data engineering architecture design and implementation to extract and ingest valuable data from structured & unstructured data sources, harnessing cloud, data and AI technologies to make data-driven decisions more accurate and efficient.
• Lead and manage engineering design patterns and architectures across the hybrid cloud stack for adoption by engineering teams. Support recruiting, mentoring, and coaching engineers to deliver high-quality solutions on time and within budget. 
• Develop and deploy hybrid cloud stack document AI solutions, including OCR, NLP, entity recognition, and information extraction in a production environment.
• Drive adoption of document data engineering best practices using programming languages such as Python, Java, or C , and familiarity with relevant frameworks and libraries for AI and big data, such as TensorFlow, Apache Spark, Databricks or Snowflake.
• Develop and execute a data engineering architecture for document AI engineering projects to streamline documentation classification, extraction, enrichment workflows, reducing manual efforts, and improving efficiency.
• Assist from opportunity grooming to implementation by leading business conversations, building document classification, extraction, enrichment and visualization solution designs, architecture proposals.
• Work in partnership with data engineering counterparts to drive current state data engineering assessment and define target state architecture and roadmaps. Manage overall architecture, design, implementation, and testing of new document ingestion capability projects.
• Build and maintain architecture artifacts, design processes and best practices, provide technical oversight to architects and engineers. Prototype solutions and develop proof-of-concept.

Education and Experience

• Bachelor’s degree in computer science, Information Technology, or a related field; advanced degree preferred.
• Advanced Degree in Applied Sciences (Data Science, Math, Statistics, Engineering, etc.) preferred.
• Minimum of ten (10) years of experience in Cloud implementations with one or more of the following platforms - Google, Azure, AWS. Deep experience with automation and orchestration tools such as Kubernetes, automated DevOps and CloudOps.
• Minimum of five (5) years of experience in designing and implementing enterprise-wide cloud data and analytics platforms such as Hadoop, Spark, and Kafka for handling large volumes of document data efficiently and extracting insights effectively. 
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying and managing document AI solutions at scale, leveraging services like managed databases, container orchestration, and serverless computing.
• Expertise in solution architecture including web services, databases, front-end, backend technologies. Certifications in Google, Azure Cloud, or AWS.
• Proven experience with large scale distributed & cloud-based technologies such as Kubernetes, Kafka, MySQL, Databricks, Containers, Snowflake, Splunk, Elastic, and Hadoop.
• Large-scale data engineering and coding experience in Python, PySpark etc.
• Experience managing a team of onshore and offshore architects, developers, and analysts.
• Ability to define competitive and innovative technical design and get stakeholder buy-in
• Exceptional collaboration and partnership skills with the ability to work in a global environment and drive consensus in cross-functional teams.

Key Behaviors and Competencies

• Demonstrate the ability to work well with others and be respected as a leader.
• Deep understanding of agile project delivery models and methodologies
• Excellent communication skills both verbal and written that clearly and concisely communicates concepts to varying levels of the organization.
• Energetic, self-starter who can independently multi-task across many different complex strategic programs to drive multiple deliverables concurrently.
• Creative problem solver with the ability to quickly identify and resolve errors through collaborative solutions.
• Data-driven decision maker; able to complete thorough research and investigation, yet quickly make decisions and present findings.
• Experience working across business, technical, IT, Digital and Operations teams to influence decisions and drive outcomes.