Job Summary
The AI/Data Engineer will support enterprise modernization initiatives by designing and developing AI-powered data reconciliation solutions. The role will combine strong data engineering fundamentals with practical GenAI experience to build utilities that compare legacy and target system data, identify discrepancies, and generate actionable reporting. This is a hands-on individual contributor role focused on Python development, GenAI technologies, data validation, reconciliation, and modernization initiatives.
Key Responsibilities
• Design and develop AI-powered data reconciliation utilities supporting enterprise modernization efforts.
• Compare data across legacy and target platforms to identify discrepancies and inconsistencies.
• Apply AI techniques, prompt engineering, and pattern recognition to detect complex data mismatches.
• Develop scalable Python-based solutions for data reconciliation and reporting.
• Build and maintain CI/CD pipelines supporting application delivery.
• Collaborate closely with architects and senior technical leaders on solution implementation.
• Contribute as a hands-on individual contributor within a fast-paced engineering team.
• Support data validation, quality assurance, and modernization initiatives across the organization.
Required Qualifications
• 7+ years of professional software engineering or data engineering experience.
• Strong hands-on data engineering experience.
• Experience with LangGraph.
• Experience consuming MCP services.
• Experience working with GenAI tools and solutions.
• Strong prompt engineering expertise.
• Advanced Python development experience.
• Experience implementing CI/CD practices and pipelines.
• Strong problem-solving and analytical skills.
• Ability to learn new technologies and adapt quickly in a fast-moving environment.
Preferred Qualifications
• Experience combining data engineering and GenAI engineering.
• Experience building AI-driven data validation, reconciliation, or automation solutions.
• Experience supporting large-scale modernization initiatives.
• Previous experience with the organization's environment preferred.
