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The Hartford · 12 hours ago

VP, AI & Data Architecture

Hartford, CT

Full-time

Onsite

Senior Level, Lead/Staff

$222K/yr - $334K/yr

12+ years exp

The Hartford is an insurance company that aims to make a difference by providing opportunities for growth and achievement. The VP of AI & Data Architecture will lead initiatives to create scalable AI and Data platforms, focusing on strategy, implementation, and governance to enhance the organization's data maturity and capabilities.

Auto InsuranceCommercial InsuranceEmployee BenefitsFinanceFinancial ServicesInsuranceLife InsuranceProperty Insurance

Responsibilities

Develop and execute a comprehensive Enterprise AI and Data Architecture strategy, which include Strategic Capability maps, Enterprise data models, and multi-cloud architecture patterns that ensure scalability, reliability, and security

Design and implement modern data architectures such as Lakehouse (OTFs) and Lakebase. Design capabilities to support real time streaming analytics, data API integrations, GenAI applications, including structured and unstructured, real time data ingestion/transformation, segmentation and tagging, storage (object store, vector databases, caching), processing, and retrieval for large language models (LLMs), Vision Language Models (VLM) and other AI/ML models. Additionally, enable model prompt tuning, fine-tuning, evaluation, RLHF, optimization and monitoring architecture

Establish and drive a strategy for Enterprise-wide Data Governance and Data Privacy programs that maximize value from data by producing trusted, high quality data products that are easily discoverable by data consumers

Drive the creation and methodical application of metrics that assess maturity and demonstrate the progression of AI & Data enabled capabilities across the enterprise

Architect and design complex data platforms leveraging Snowflake, AWS, GCP, and other cutting-edge technologies. Design multi-cloud data integration and lifecycle management

Perform ongoing market scans for emerging solutions, technologies, and architectural concepts to incorporate into an evolving portfolio of data and AI capabilities

Provide technical leadership and guidance on AI & Data architecture best practices, including data governance, data security, and data integration

Cultivate and lead communities of practice that evangelize the benefits and promote the adoption of re-useable solution patterns, along with establishing a feedback mechanism for continuous improvement and iterations of such patterns

Provide leadership and mentorship to federated teams of architects and engineers, fostering a culture of innovation, collaboration, and continuous upskilling and learning

Oversee the creation and maintenance of comprehensive documentation of AI and Data architecture designs, standards, and best practices

Continuously evaluate and recommend new data technologies and trends to improve our data capabilities

Qualification

AWSGCPSnowflakeAI/ML ArchitectureData GovernanceData IntegrationData TransformationLeadershipCommunicationMentorship

Required

Expert understanding and hands on experience with multiple cloud platforms (e.g., AWS, GCP, Snowflake)

Knowledge of leading data integration and transformation tooling. (real-time data streaming, agentic frameworks, Data APIs, vector stores, and RAG architectures, self-serve analytics and AI.)

Ability to lead large scale transformation initiatives

Excellent communication, presentation, and leadership skills

Ability to influence and collaborate with Executive leadership

Experience with advanced AI/ML and Agentic and data pipelines

Deep understanding of AI/ML and Data software engineering principles and operational best practices using open source, cloud technologies, modern platform tools, data pipelines, lakehouse architectures (OTF), enterprise data warehousing, and large-scale data transformations, pre-training, post-training, evaluation, serving, and monitoring

Knowledge of DevOps, DataOps, MLOps, LLMOps, and AIOps

Ownership mentality, taking accountability for project success and the continuous improvement of data engineering processes, architecture, and operating models

Bachelor's or Master's degree in Computer Science, Information Systems, a related field, or equivalent work experience

12+ years of experience in data architecture, with a focus on enterprise-level data solutions

6 + years of experience in AI/ML Architecture

10+ years of experience of people leadership (formal or matrix)

Deep expertise in designing and implementing data and system architectures for AI/ML, Generative AI, and Agentic applications