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Regular or Temporary:

Regular

Language Fluency:  English (Required)

Work Shift:

1st shift (United States of America)

Please review the following job description:

Deliver technically advanced solutions in support of Truist’s Anti-Money Laundering (AML) Technology initiatives, with a focus on Machine Learning and Generative AI use cases. Partner with application teams, product owners, and internal stakeholders to design, guide, and implement model-driven solutions. Provide subject matter expertise throughout the model lifecycle, from concept through governance, approval, and deployment.

ESSENTIAL DUTIES AND RESPONSIBILITIES
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

• Serve as a technical advisor across AML Technology teams for Machine Learning and Generative AI initiatives, supporting multiple use cases and applications.

• Collaborate with application teams, vendors, and internal partners to design, develop, and deploy predictive and AI-driven models aligned with financial crime detection objectives.

• Provide expertise in model development, integration, and deployment — including supporting teams in configuring solutions, performing analysis, and enabling scalable implementations.

• Guide and influence best practices for Machine Learning and AI adoption within AML Technology, helping define standards, approaches, and reusable frameworks.

• Lead and contribute to model lifecycle activities, including development, testing, validation support, implementation, and post-deployment monitoring.

• Support development of required model documentation, including Model Definition Documents (MDD), and ensure alignment with internal standards and regulatory expectations.

• Partner with application teams to navigate AI governance processes, including model review, validation, risk assessment, and approval workflows required for production deployment.

• Build and support monitoring, performance evaluation, and controls for models and associated applications in production environments.

• Ensure adherence to security, compliance, and enterprise technology standards across all implemented solutions.

• Help solve complex technical and operational challenges related to model integration, data pipelines, and AI deployment in enterprise systems.

• Act as a mentor and resource for teammates, providing guidance on Machine Learning techniques, financial crime use cases, and technical implementation strategies.

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. 

• Bachelor’s degree in Computer Science, Information Systems, or related field, or equivalent experience. 

• Minimum of 3 years of experience in information security, systems analysis, or related technical field. 

• Foundational knowledge of data security principles, system architecture, and security controls. 

• Experience or exposure to system monitoring, data analysis, or risk identification activities.

Preferred Qualifications:

• Strong experience with Machine Learning techniques, model development, and deployment in enterprise environments.

• Exposure to Generative AI technologies and frameworks (e.g., LLMs, prompt engineering, model orchestration).