Manager, AI Solutions

Arbitration Forums Inc.•Tampa, FL

2d•Remote

About The Position

This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion). The Manager, AI Solutions 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 AF’s 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 AF’s stakeholders to identify opportunities to embed intelligent decisioning in the claims management ecosystem, utilizing data science, machine learning, robotic process automation, and other AI practices to support our members in reducing the cost of operations, increasing processes quality, and providing meaningful and actionable data-based insights. The Manager, AI Solutions articulates strategies for the design, development, optimization and testing of AI models, ensuring the production of accurate, relevant, and compliant outs across AI initiatives. This role is accountable for the implementation of configurable and interoperable AI solutions that optimize the value delivered to our members, and works with AI product architects, advanced analytics, data governance, and other stakeholders to enable AF’s journey to innovation. This role encompasses data science, Generative AI, Speech and Text analytics, Robotic Process Automation, and other related areas of the AI universe and collaborates with AF’s functions to execute strategic plans that bring innovative solutions and excellent value to our members’ organizations.

Requirements

More than 10 years of experience in AI technologies and AI business operations.
10 years of experience in the operationalization of AI models and integration with business processes and applications.
Domain and industry knowledge, with 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 diverse deployment options for AI-based products, from marketplace, to API and programmatic approaches.
Proficiency in the definition and implementation of prioritization frameworks.
Expertise in cloud application solutions, API design and management, and marketplace business and deployment models.
Experience implementing MLOps processes and frameworks.
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.
Experience with data visualization tools such as Webfocus, Power BI or Tableau.
Experience defining and managing a data technology stack, enabling the definition and implementation of controls and best practices.
Understanding of cloud-based data engineering processes, as well as exposure to data platforms such as Databricks or Snowflake.
Advanced SQL skills including writing and tuning complex queries, Oracle database experience preferred.
Experience utilizing data transformation and load technologies such as Talend, DBT, Matillion, etc.
Experience interacting with Data Science, ML tools such as Dataiku, Azure ML, Snowflake Cortex AI, Databricks AI, etc.
Advanced understanding of data cataloging and lineage plotting processes and tools.
Proficiency in utilization of generative AI models (GPT-4, DALL-E, etc.).
Working knowledge of Azure AI Foundry and ML Studio.
Strong working knowledge of programming languages such as Python, R, or SQL and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).
Experience with AI tools, such as MS Azure ML, Snowflake CortexAI, Dataiku.
Strong knowledge of data governance, data security, and compliance practices.
Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI).
Proficiency in programming languages such as Python, R, or SQL.
Working knowledge of cloud services (MS Azure, AWS) and data platforms (Snowflake, Databricks).
Exposure to techniques for text parsing, sentiment analysis, and the use of transformers such as (BERT-base. ELMo, ULM-FIT.
Strong knowledge of data governance, data security, and compliance practices.
Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI).
Strong working knowledge of automation tools such as MS Power Automate and Appian.
Communicate clearly and directly.

Responsibilities

Partner with stakeholders to identify high value use cases to provide data insights, automation, and forecasting capabilities, with a critical eye for the ones that will result in the highest business value.
Enable the incorporation of configurable and interoperable AI products from design to deployment, ensuring the alignment of advanced analytics, AI product architecture, IT and product implementation and adoption functions.
Define best practices in the area of LLMs, prompt engineering, forecasting, and RPA solutions.
Set the practice for improving model effectiveness and performance through the model lifecycle, including observability and monitoring processes to identify model performance and potential degradation. Establish action plans on mitigation of potential model degradation.
Collaborate with business architects and process owners to enable the identification of areas and process steps in where RPA brings value.
Enable the creation of safety filters and ethical use of models to prevent bias, and to promote fairness, following our AI Acceptable Use and Ethics policies.
Work with the data governance lead to establish and enforce data governance standards, guidelines, processes, and best practices to ensure data quality and integrity as they apply to AI.
Establish and implement explainability frameworks, like Model Context Protocols and SHAP.
Ensure that data security protocols are followed in the definition and implementation of AI solutions in accordance with regulatory requirements and company policies.
Collaborate with stakeholders to generate strategies for embedding AI solutions into business processes and applications.
Manage the capacity of the team by prioritizing the highest value initiatives, as well as the ones that enable the building of internal capabilities.
Deliver AI-powered solutions that contain a high level of interoperability, configurability, and modularization.
Engage with partners to understand what marketplace deployment models mean from an AI rollout perspective.
Collaborate with stakeholders in defining implementation options for our members, including reviewing solution paths and roadmaps.
Enable the identification and prioritization of AI-powered use cases to ensure integration and deployment requirements are considered.
Enable effective AI text and speech services through utilization of ASR engines using standard and fit-for-purpose frameworks.
Partner with IT QA and AI QA Engineers to define a testing practice that is efficient, cost-effective, and automated; implement the necessary tools to enable test efficiency.
Advocate and promote AI literacy internally and externally.
Establish goals for the AI Solutions team and its members, and clearly articulate performance objectives.
Communicate clearly and directly.
Delegates effectively, mentoring, and coaching team members to enable their success.
Live AF’s values and behaviors, holding team members accountable for conducting themselves within the behaviors of the organization.
Establish engagement models to effectively interact and drive accountability for team members across AF.