AVP AI and Data Engineering - Employee Benefits

AVP Data Engineering - GE05AE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

Join The Hartford Insurance as we lead the AI transformation in our industry!

We are seeking a highly skilled leader, Assistant Vice President (AVP) of AI and Data Engineering, to join our Employee benefits data team. The ideal candidate has experience in developing scalable data environments, launching data products, enabling AI/ML solutions, and shaping data analytics strategies. The AVP will lead the development and implementation of advanced AI and data engineering solutions to drive business transformation and enhance customer experiences.

• Leadership & Strategy Lead the execution of enterprise-wide data strategy, ensuring alignment with AI-driven transformation goals. Oversee data architecture standards, develop scalable data consumption patterns, and drive innovation in AI solutions. Effectively communicate strategy and progress to diverse stakeholders and promote data capabilities through thought leadership and presentations.
• Data modernization: create the roadmap and plan to modernize the legacy data platform to strategic cloud platform. Solve the current data complexities and enable data products for all consumption architypes and stakeholders.
• Real-Time Data Streaming: Design and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery. Extract insights from unstructured data and integrate it with structured sources to enable comprehensive analytics.
• Third-Party Data Exchange: Partner with Technology teams to implement a data exchange strategy with Third-Party Administrators (TPAs).
• Team Leadership & Development: Build, mentor, and lead a high-performing team of data engineers and architects.
• Drive efficiency and Productivity: Identify and champion developer productivity opportunities across the end-to-end data management lifecycle. This includes researching and implementing innovative solutions such as AI-driven auto-generation of ETL pipelines, advanced DevOps practices for data and automated data quality frameworks.
• Data Infrastructure Development & Management: Oversee the design, development, and maintenance of data pipelines, warehouses, and lakes.
• AI/ML Data Enablement: Architect data solutions for AI and machine learning models focused on operational optimization and customer experience enhancement.
• Collaboration & Communication: Partner with business stakeholders to translate data needs into technical requirements.
• Technology Evaluation & Adoption: Stay current with emerging trends in data engineering and AI/ML infrastructure, and recommend innovative tools and technologies to enhance data capabilities
• Data Governance & Compliance: Data Governance & Quality: Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices that enable data consumers to quickly and effectively find, access, interpret, and utilize data.
• Budget Management: Manage the budget for the AI Data Engineering function.
• Performance Monitoring & Optimization: Monitor data pipeline and infrastructure performance, driving continuous improvement and optimization initiatives.

• Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.
• 15+ years in data engineering, designing, and developing large-scale data ecosystems.
• A minimum of 3 years of experience in progressively responsible leadership roles (through to the senior management level), managing medium to large-sized teams and cross-functional initiatives
• Excellent presentation and storytelling skills to communicate complex technical concepts to both technical and non-technical audiences
• Mastery level Data Engineering and Architecture skills - a deep understanding of data architecture patterns, data warehouse, integration, data lake, data domains, data products, BI, and cloud technology capabilities.
• Experience integrating ML solutions with cloud platforms like AWS SageMaker, GCP Vertex AI and leveraging their pre-built capabilities.
• Technical expertise in: Large Language Models (LLMs) and Generative AI platforms (Anthropic, OpenAI), Prompt engineering and LLM optimization techniques, Retrieval-Augmented Generation (RAG) architectures, Vector database implementations (Vertex AI, Postgres, OpenSearch, Pinecone etc.),AI Agent development and orchestration, Enterprise API development and integration.
• Experience handling model hallucinations, experience with grounding and ranking APIs.
• Experience with GCP, Cloud AI, Vertex AI, and Big Query required.
• Hands-on experience in Lang chain and building AI agents.
• Experience in Vertex AI agent builder and Google Agent space.
• Knowledge in building hybrid data lake-houses involving more than one cloud vendor partner.
• Strong communication skills to describe and explain complex AI/ML concepts and models to business leaders.
• Strong understanding of traditional machine learning algorithms and their applications.
• Expertise in computer vision, including object detection, image segmentation, and image recognition.
• Proficiency in NLP techniques, including sentiment analysis, text generation, and language understanding models. Experience with multimodal language modeling and applications.
• Understanding of Generative AI concepts and LLM Models tailored to a wide variety of automotive applications.
• Hands-on experience with unstructured data mining and content summarization.
• Strong experience with the design and development of complex data ecosystems leveraging next-generation cloud technology stack across AWS or GCP Cloud and Snowflake.
• Preferred experience in the financial services or insurance industry.