Senior AI Engineer - Risk: Compliance, and Fraud

Role: Senior AI Engineer - Risk: Compliance, and Fraud

Location: Plano, TX (Hybrid)

Type: Contract

Description:

• We are seeking a Senior AI Engineer to lead the technical design and execution of our AI-driven Anti-Money Laundering (AML) technology roadmap.
• Leveraging your deep Python expertise, you will architect robust, secure, and production-grade AI systems natively on AWS that are capable of auditing transactions in real-time, detecting complex financial crime networks, and automating legal narrative generations.
• You will ensure these systems meet the highest standards of regulatory compliance, safety, and transparency.

Key Responsibilities:

• Architect AI Solutions: Design scalable AI systems and Agentic LLM workflows on AWS infrastructure to handle real-time AML transaction analysis, link analysis, and network fraud detection.
• False Positive Reduction: Architect advanced classification and anomaly detection models to significantly decrease operational noise for human compliance analysts.
• Defensible & Compliant AI: Own the guardrails and transparency architecture, ensuring every automated flag or generated document strictly complies with global banking regulations and data privacy rules.
• System Integration: Oversee the secure integration of vector databases, graph databases (for network analysis), and core banking APIs within AWS VPC environments.
• Technical Mentorship: Guide mid-level engineers, enforce clean coding practices, and lead code reviews for the compliance engineering team.

Required Qualifications & Skills:

• Python Mastery: 5+ years of software/AI engineering experience writing production-grade code in Python, with a proven track record of deploying machine learning models into high-throughput environments.
• Advanced AI Knowledge: Expert-level understanding of transformer architectures, agent frameworks (e.g., LangGraph, AutoGen), RAG architecture, and fine-tuning open-source models.
• AWS Infrastructure: Extensive experience scaling cloud-native AI workloads using AWS infrastructure (e.g., Amazon SageMaker, AWS Lambda, EKS/ECS, and Bedrock).
• Complex Data & Graphs: Strong experience with Graph Databases (e.g., Neo4j or Amazon Neptune) for entity resolution or transaction network analysis is highly desirable.
• Industry Domain: Previous experience working within Financial Services, FinTech, or Banking with a strong understanding of AML regulations (e.g., Bank Secrecy Act, FinCEN guidelines).