GenAI/AML Solutions Architect

This range is provided by Vision Talent Co.. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range CA$100.00/hr - CA$130.00/hr Vision Talent’s client is seeking a highly experienced Senior GenAI & Data Solutions Architect to design, build, and enhance next-generation solutions in the Anti-Money Laundering (AML) and Fraud Analytics space. This role will focus on leveraging Generative AI , agentic AI design patterns , and modern cloud-based data platforms to deliver scalable, accurate, and governed FinCrime solutions aligned with enterprise AI standards. The ideal candidate brings deep technical expertise across cloud data platforms, GenAI architectures, and FinCrime analytics, with the ability to collaborate across business and technology teams to deliver impactful, reusable AI-driven solutions. ****This is a contract position, initial term is 6 months with strong likelihood of extension. Hybrid with 4 days/week required on site in downtown Toronto. Key Responsibilities GenAI & AI Solution Design Design and implement Generative AI solutions to enhance AML and Fraud Analytics use cases. Develop Retrieval-Augmented Generation (RAG) applications using vector databases, indexing strategies, and semantic search. Apply agentic AI design patterns and frameworks to build intelligent, autonomous FinCrime agents. Design and develop reusable FinCrime AI agents that can be leveraged across multiple use cases. Integrate MCP frameworks with agentic AI solutions where applicable. Design and build modern cloud-based data platforms with 6+ years of hands‑on experience. Implement data ingestion, transformation, and modeling pipelines within lakehouse architectures . Work primarily with Azure and/or AWS , with preference for candidates familiar with enterprise‑scale cloud environments. GenAI Platforms & Tooling Build GenAI solutions using platforms such as Azure OpenAI (Foundry) and AWS Bedrock (e.g., Anthropic models). Evaluate and recommend open‑source LLMs and frameworks , selecting the most appropriate solution for each use case. Implement index‑based and vector‑based search techniques to improve accuracy and relevance of GenAI outputs. Model Accuracy, Governance & Operations Define and execute testing strategies for GenAI solutions, focusing on accuracy, reliability, and bias mitigation. Continuously improve GenAI output quality through prompt engineering, retrieval optimization, and evaluation frameworks. Contribute to model documentation, governance, evaluation, and compliance processes. Support LLMOps and MLOps practices, including deployment, monitoring, and lifecycle management. Work closely with Business, FinCrimes IT, platform teams, and cross‑functional technical teams . Quickly understand and align with enterprise AI processes and governance standards , developing solutions accordingly. Stay current with industry trends and rapidly adopt best practices in GenAI, data engineering, and FinCrime analytics. Required Qualifications 6+ years of experience designing and building modern data platforms in the cloud (Azure or AWS preferred). Strong hands‑on experience with: Data ingestion, transformation, and modeling in lakehouse environments Python, PySpark, Docker Proven experience designing and deploying: RAG applications Vector databases and indexing strategies Agentic AI solutions Strong understanding of GenAI testing methodologies , accuracy measurement, and optimization techniques. Experience with LLMOps / MLOps practices. Strong communication skills with the ability to work across technical and non‑technical teams. Nice to Have FinCrime domain knowledge (AML, Fraud, Financial Crimes). Experience in regulated enterprise environments with strong AI governance requirements. Familiarity with open‑source AI ecosystems and emerging GenAI frameworks. This is a hybrid role with 4 days a week required on site downtown. Initial 6 month contract term with a strong likelihood of extension. Apply today to learn more Seniority level Mid‑Senior level Employment type Contract Job function Information Technology #J-18808-Ljbffr