This role involves leading the design, development, and deployment of advanced AI/ML solutions with a specialized focus on Anti-Money Laundering (AML), Fraud Detection, and Agentic AI capabilities, all within the AWS ecosystem. You will be responsible for the complete lifecycle of intelligent systems, from initial problem identification and conceptualization through to production rollout and ongoing performance enhancement.

This position offers a unique opportunity to drive innovation and deliver cutting-edge AI-driven outcomes. The ideal candidate will possess a strong technical background coupled with a strategic mindset to translate business needs into effective AI strategies.

Spearhead the architecture and implementation of sophisticated AI/ML solutions on AWS.

Develop deep expertise in AML and Fraud typologies to build robust detection systems.

Create and execute complex simulation models for performance analysis and prediction.

Design and build predictive, classification, recommendation, forecasting, and optimization models.

Establish and manage scalable ML pipelines covering data ingestion, feature engineering, model training, deployment, and monitoring.

Manage the end-to-end delivery of AI projects, from initial discovery to successful production deployment.

Engineer autonomous AI agents capable of complex reasoning, planning, memory management, and tool orchestration.

Collaborate effectively with business stakeholders, data engineers, architects, and product teams to deliver scalable AI solutions.

Construct multi-agent systems to automate workflows and provide intelligent decision support.

Utilize AWS services such as SageMaker, Amazon Bedrock, and AWS Lambda for AI workload development.

Implement comprehensive frameworks for model monitoring, drift detection, retraining, and governance.

Significant experience (6-9 years) in leading AI/ML projects, particularly on the AWS platform.

Proven track record in developing solutions for AML and Fraud detection scenarios.

Demonstrated experience in creating and executing simulation models.

Expertise in building various types of machine learning models, including predictive, classification, recommendation, forecasting, and optimization.

Proficiency in developing scalable ML pipelines for data management and model lifecycle.

Experience in designing and implementing autonomous AI agents with advanced capabilities.

Strong understanding of multi-agent systems for automation and decision support.

Familiarity with AWS SageMaker, Amazon Bedrock, and AWS Lambda.

Knowledge of model monitoring, drift detection, retraining, and governance frameworks is essential.

Excellent collaboration and communication skills to work with diverse teams and stakeholders.