AI Product and Data Architecture Manager

We are seeking a strong AI Product and Data Architecture Manage for a fully remote job

US Citizens or Green Card Holders ONLY!!

No C2C

No Third Party Agencies

The AI Product and Data Architecture Manager is responsible for understanding the opportunities brought by emerging technologies and Artificial Intelligence to the end-to-end insurance Claims process. This role is critical in the evolution of current product line functionality via identification of AI-powered capabilities.

As part of an AI-powered solution designing and implementation organization, this role will partner with stakeholders to identify opportunities to embed intelligent decisioning in the claims management ecosystem, modularizing current architecture via re-engineering, modularization, and shifting functional architectures to cloud.

The AI Product and Data Architecture Manager articulates the strategy for the definition and implementation of configurable and interoperable AI solutions and plug and play scenarios that provide our members and partners with options to realize the value of offerings, while minimizing technical debt and optimizing the value delivered.

This role collaborates with AI Innovation, Advanced Analytics, Operations, Marketing, Membership Experience, and IT functions to execute strategic plans that bring innovative solutions and excellent value to our members’ organization.

The AI Product and Data Architecture Manager is a critical player in the journey to data-driven and AI-powered innovation, identifying and implementing strategies to enable the design, development, and implementation of complete and interoperable functional and technical capabilities.

QUALIFICATIONS

• More than 10 years of experience in operationalization of AI models and integration with business processes and applications.

• More than 8 years of experience in product architecture, product management, and systems interoperability.

• Domain and industry knowledge, with deep understanding of how Insurance companies and Claims Management divisions work.

• Experience with technology driven transformations and end to end AI solutions lifecycle.

• Deep understanding of machine learning/AI principles and concepts, and how AI solutions integrate with existing business processes or applications.

• Proficiency in the definition and implementation of prioritization frameworks.

• Expertise in cloud application solutions, API design and management, and marketplace business and deployment models.

• Functional knowledge of composable products with a high level of configurability.

• Working knowledge and proficiency in the development of implementation and adoption plans for composable offerings, including documentation of configuration requirements.

• Proficiency in the operations of a not-for-profit organization.

• Knowledge of advanced data analytics platforms and visualization tools to create reports and dashboards in a self-service approach.

Technical Skills

• Working knowledge of cloud services (MS Azure, AWS) and data platforms (Snowflake, Databricks).

• Experience with AI tools, such as MS Azure AI Foundry and ML Studio, Snowflake Cortex AI, Dataiku.

• Proficiency in programming languages such as Python, R, or SQL.

• Experience designing integrations using tools such as MS Azure API Management, Boomi, MuleSoft, and Apigee.

Leadership

• Establish goals for the AI Product and Data Architecture team and its members, and clearly articulate performance objectives.

• Delegates effectively, mentoring, and coaching team members to enable their success.

• Conduct frequent performance conversations with team members, helping with corrective actions when needed.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Partner with stakeholders to define strategies for the definition of configurable and interoperable AI products.

• Collaborate with stakeholders and IT to re-engineer the high value functionality of current products and move it from on-prem to cloud.

• Works with IT in the development of strategies and roadmaps to sunset, refactor, or redefine current functionality in new AI-based architectures on cloud or hybrid environments.

• Define best practices for the generation and maintenance of functional roadmaps for AI solutions that prioritize the highest value items while removing technical debt.

• Partner with stakeholders to generate strategies for embedding AI solutions into business processes and applications, with a focus on progressive functionality deployment and modularization.

• Manage the orchestration of activities to ensure alignment of AI product architecture, software engineering and implementation across the AI product lifecycle.

• Lead the planification effort of AI-based initiatives, including timeframes and deliverables, and work closely with Advanced Analytics, IT, Marketing, Operations, and AI COE to ensure capacity is reserved and obstacles that derail delivery are addressed.

• Create, socialize, and manage AI integration architectures, providing AI-powered functionality with a high level of interoperability, configurability, and modularization.

• Engage with partners to define marketplace deployment models, ensuring accessibility and integration with existing ecosystems.

• Collaborate with Customer Success and Product Implementation and Adoption teams to define and orchestrate strategies for the success of implementations in our members, including reviewing solution paths and roadmaps.

• Works closely with software engineers, AI and data engineers, product managers, and other stakeholders to understand requirements and define scalable APIs that meet user needs and business objectives.

• Collaborates with IT to define and execute strategies for production deployment of solutions, ensuring that solutions can be deployed in the preferred way of our members.

• Define, manage, and improve the AI product architecture lifecycle end-to-end and represent it in roadmaps and collateral materials.

• Enable the identification and prioritization of AI-powered use cases to ensure integration and deployment requirements are considered.

• Partner with AI QA Engineers and IT QA Testers to ensure that the AI product testing practice is efficient, cost-effective, and automated.

• Define and manage feedback loops to understand the impact that AI-based

functionality has on our members and end users and socialize the information across the company.

• Define and maintain data reference architectures and models that support needs in the areas of advanced analytics, AI, and data products.

• Ensure that data architectures abide by interoperability requirements and allow the integrity of the data continuum.

• Partner with Advanced Analytics, Data Governance, and IT to implement data security protocols in compliance with security and regulatory requirements.