AVP AI and Data Engineering

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.   

         

We are seeking a highly skilled and experienced Data and Technology leader, Assistant Vice President (AVP) of AI and Data Engineering, to join our dynamic team. The AVP will lead the development and implementation of advanced AI and data engineering solutions to drive business transformation and enhance customer experiences. This Technology leader will manage a team of 80+ data engineers.

This role requires a strategic thinker with a deep understanding of AI technologies, data engineering practices, and the ability to lead cross-functional teams. The ideal candidate will have a strong background in real-time data streaming, expertise in building complex agentic frameworks, Data APIs, vector stores, graph knowledge bases, and Retrieval-Augmented Generation (RAG) architectures, and a proven track record of enabling self-serve analytics and AI use cases.

This role can have a Remote or Hybrid work arrangement.  Candidates who live near one of our office locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday)  Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise.

Key Responsibilities:

Leadership & Strategy:

• Lead and manage a team of data engineers, providing technical guidance, mentoring, and career development opportunities.
• Collaborate with cross-functional teams, including data science, product development, and IT, to align enable data for AI initiatives.
• Develop and implement strategies that supports structured, unstructured data mining, real-time data streaming, vector and graph databases, and AI-powered applications.
• Be a thought leader, driving positive change and simplification while improving delivery speed.
• Stay up to date on emerging AI trends, attending conferences, and driving thought leadership to enhance organizational impact and visibility.
• Design AI prototypes and conduct experiments, with the ability to guide frameworks for production-ready solutions.
• Lead innovation by overseeing the development and deployment of cutting-edge AI solutions, ensuring scalability, effectiveness, and ethical soundness.

Build Strategy for Customer Domain Data:

• Establish the target state for Customer domain data.
• Create a comprehensive Customer 360 solution along with digital data.
• Implement a robust Master Data Management (MDM) system.
• Enhance the entity solution for improved data accuracy and consistency.
• Build data pipelines and AI agents to enable virtual assistants for Contact Center Agents.

Build and Support AI Use Cases:

• Leverage various foundational models, fine tuning thru prompt engineering and Knowledge RAGs.
• Build and maintain vector and graph database infrastructure for efficient storage and retrieval of embeddings used in RAG applications.
• Develop APIs and integration layers for enterprise AI services, ensuring compliance with regional data protection requirements.
• Create and optimize data streaming architectures for real-time AI applications
• Architect, implement, and maintain knowledge bases such as vector and graph databases to support complex data relationships and queries.

Design and Build AI Agents:

• Design and develop scalable AI agent frameworks to manage high call volumes by assisting human agents in real-time, reducing the need for manual searches and enabling more efficient and effective responses and improve agents' decision-making capabilities, boosting resolution times, productivity, and providing a personalized customer service experience.
• Enable build Voice Bots and Virtual Assistants: to help teams work faster, more accurately, and more confidently without sacrificing the human touch
• Stay updated on AI advancements, optimize AI agent performance through testing, and provide mentorship to junior members.

Real-Time Data Streaming:

• Design, build, and maintain scalable and robust real-time data streaming pipelines using technologies such as Apache Kafka, AWS Kinesis, Spark streaming, or similar.
• Ensure the efficient ingestion, processing, and delivery of data to various stakeholders and applications in real-time.

Unstructured Data Mining:

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