Artificial Intelligence/Machine Learning Engineer

Artificial Intelligence/Machine Learning Engineer

General Description This role is for an AI Data Reconciliation Specialist. It is technical in nature and will require firsthand Artificial Intelligence (AI) coding. The position also requires extraordinarily strong experience in eliciting data reconciliation requirements from stakeholders, developing AI solutions, and output utilizing Azure services. The candidate must have solid direct experience designing and implementing an automated, repeatable, and auditable data reconciliation framework utilizing AI. This will include processing, reconciling, and verifying the integrity of data used for analysis, as well as performing ad‐hoc analysis and presenting results in a clear manner. Focused on generating, maintaining, and delivering detailed and accurate reporting on the information gathered and reported by artificial intelligence systems, with the goal of maximizing ROI from the rush of new data generated. The employee will rely on experience and judgment to plan and accomplish goals, independently perform a variety of complicated tasks, and lead and direct the work of others. They will also be expected to demonstrate their knowledge and skills in functional aspects of data reconciliation and AI development during the interview process. Functional ResponsibilitiesERS is seeking an AI Data Reconciliation Specialist with impeccable AI skills, including experience in developing AI data reconciliation frameworks. The candidate must be confident in having detailed conversations with users at the functional level and with developers at the technical level, and should have experience in writing advanced SQL, analyzing data, and developing AI code using Azure services. The employee will be responsible for Designing and implementing an automated, repeatable, and auditable data reconciliation framework Building AI-assisted reconciliation pipelines for: Row‐level validation Aggregate validation Anomaly detection Root‐cause analysis Supporting large‐scale data migrations and ongoing system integrations Replacing manual, error‐prone reconciliation processes with scalable automation Establishing reconciliation controls, logging, traceability, and auditability