Requirements
The FWA AI Engineer is responsible for designing, building, testing, and deploying AI solutions for Fraud, Waste & Abuse detection and investigation. This role requires translating business requirements and data science models into scalable production solutions on GCP, integrating AI capabilities into operational workflows. Key accountabilities include solution design, AI development and engineering, production deployment, testing, and continuous improvement. A Bachelor's Degree in Computer Science, Software Engineering, Artificial Intelligence, or Data Science is required, along with experience in delivering AI/ML solutions into production.
Description
Job DescriptionRole Purpose:The FWA AI Engineer is responsible for designing, building, testing, and deploying AI solutions that support Fraud, Waste & Abuse (FWA) detection and investigation. The role translates approved business requirements and data science models into scalable production solutions, integrating AI capabilities into operational workflows while ensuring reliability, performance, and business value. Working closely with the FWA Lead, FWA Data Scientist, investigators, and business stakeholders, the role drives the successful implementation and continuous enhancement of FWA AI use cases.Key Accountabilities:1- FWA Solution Design & Feasibility Assessment;Assess technical feasibility of approved FWA use cases.Evaluate data availability, technical requirements, and implementation complexity.Define solution approaches for AI-driven FWA detection.Develop technical requirements and implementation plans.Recommend optimal AI techniques and technologies for delivery.2- AI Solution Development & Engineering;Build and optimize AI solutions supporting FWA detection and investigation activities.Translate models and analytical logic into scalable cloud-native solutions on GCP.Implement machine learning, anomaly detection, graph analytics, and document intelligence solutions.Develop APIs, scoring services, and integration components required for operational deployment.Ensure solutions are scalable, maintainable, and aligned with technical standards.Collaborate with the FWA Data Scientist to operationalize validated models.3- Production Deployment & Integration;Deploy AI solutions into operational environments.Integrate AI outputs with internal systems and workflows.Coordinate with Data Engineering and TIDES (IT) teams to enable production deployment.Support release planning and deployment activities.Ensure successful transition from development to production.4- Testing & Quality Assurance;Conduct technical testing of AI solutions.Support user acceptance testing with business stakeholders.Validate output accuracy, reliability, and performance.Identify and resolve implementation issues.Ensure solutions meet defined business and technical requirements.5- Solution Maintenance & Continuous Improvement;Support ongoing enhancement of deployed FWA AI solutions.Implement model improvements identified by the Data Science team.Address technical issues and optimize solution performance.Incorporate new fraud detection capabilities and business requirements.Maintain technical documentation and solution knowledge assets.SkillsPythonSQLGoogle Cloud Platform (GCP)Vertex AIMachine Learning ImplementationAI Solution DevelopmentAPI & System IntegrationNLP & LLM ApplicationsDocument Intelligence & OCRSoftware Development Best PracticesTesting & Quality AssuranceProblem SolvingStakeholder ManagementCommunication & Presentation SkillsCross-Functional CollaborationExperience delivering AI/ML solutions into production environments.Experience with Google Cloud Platform (GCP) is preferred.Experience in health insurance, claims, FWA, risk analytics, or financial crime analytics is preferred.Knowledge of healthcare claims, provider, and pre-authorization processes is advantageous.Knowledge of SAS is advantageous.EducationBachelor's Degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science