Manager - FWA AI Engineer

Position Overview

We are seeking a highly skilled and motivated Manager - FWA AI Engineer to lead the design, development, and deployment of cutting-edge AI solutions focused on Fraud, Waste, and Abuse (FWA) detection and investigation. In this pivotal role, you will bridge the gap between advanced data science models and scalable production systems, ensuring seamless integration of AI capabilities into operational workflows. Your expertise will drive the successful implementation of FWA AI use cases, delivering measurable business value while maintaining reliability, performance, and scalability. This position requires a blend of technical proficiency, strategic thinking, and cross-functional collaboration to transform approved business requirements into high-impact AI solutions.

Key Responsibilities

The FWA AI Engineer will play a central role in the following areas:

• FWA Solution Design & Feasibility Assessment:
  • Evaluate the technical feasibility of approved FWA use cases by analyzing data availability, technical requirements, and implementation complexity.
  • Define solution approaches for AI-driven FWA detection, ensuring alignment with business objectives and technical constraints.
  • Develop detailed technical requirements and implementation plans, recommending optimal AI techniques and technologies for delivery.
• AI Solution Development & Engineering:
  • Design, build, and optimize AI solutions that enhance FWA detection and investigation activities, leveraging machine learning, anomaly detection, graph analytics, and document intelligence.
  • Translate validated data science models into scalable, cloud-native solutions on Google Cloud Platform (GCP), ensuring adherence to technical standards and best practices.
  • Develop APIs, scoring services, and integration components to facilitate operational deployment and seamless interaction with internal systems.
  • Collaborate closely with the FWA Data Scientist to operationalize models and ensure their seamless integration into production environments.
• Production Deployment & Integration:
  • Lead the deployment of AI solutions into operational environments, ensuring smooth transition from development to production.
  • Integrate AI outputs with existing internal systems and workflows, coordinating with Data Engineering and IT teams to enable successful deployment.
  • Support release planning and deployment activities, ensuring minimal disruption and maximum efficiency in operational workflows.
• Testing & Quality Assurance:
  • Conduct rigorous technical testing of AI solutions to validate output accuracy, reliability, and performance.
  • Support user acceptance testing in collaboration with business stakeholders to ensure solutions meet defined requirements.
  • Identify and resolve implementation issues, ensuring solutions are robust, maintainable, and aligned with business needs.
• Solution Maintenance & Continuous Improvement:
  • Provide ongoing support for deployed FWA AI solutions, implementing model improvements and addressing technical issues as they arise.
  • Optimize solution performance and incorporate new fraud detection capabilities to adapt to evolving business requirements.
  • Maintain comprehensive technical documentation and solution knowledge assets to ensure long-term sustainability and scalability.

Required Skills & Qualifications

To excel in this role, candidates must possess the following technical and professional competencies:

• Technical Proficiency: Strong programming skills in Python and SQL, with hands-on experience in developing AI/ML solutions.
• Cloud & AI Platforms: Expertise in Google Cloud Platform (GCP), particularly Vertex AI, for building and deploying AI models.
• AI/ML Implementation: Experience in machine learning, anomaly detection, graph analytics, and document intelligence (OCR/NLP).
• System Integration: Ability to develop APIs, scoring services, and integration components for seamless system interoperability.
• Software Development: Adherence to best practices in software development, including testing, quality assurance, and maintainability.
• Problem Solving & Collaboration: Strong analytical and problem-solving skills, with the ability to work effectively in cross-functional teams.
• Stakeholder Management: Excellent communication and presentation skills to engage with business stakeholders, data scientists, and IT teams.

Preferred Experience & Education

While the ideal candidate will have a proven track record in delivering AI/ML solutions into production environments, experience in the following areas is highly advantageous:

• Prior experience with Google Cloud Platform (GCP) and its AI/ML services.
• Background in health insurance, claims processing, FWA detection, risk analytics, or financial crime analytics.
• Knowledge of healthcare claims, provider, and pre-authorization processes.
• Familiarity with SAS for data analysis and modeling.

Education & Professional Background

Candidates should hold a Bachelor's Degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field. A Master's Degree or advanced certification in a relevant discipline is a plus. The ideal candidate will combine technical expertise with a passion for driving innovation in FWA detection and prevention.