Lead AI Developer

Required Skills & Experience

-8+ years of experience in software/AI/ML development, including cloud and distributed architecture and platform solutions. -Hands-on experience with major cloud platforms: Azure, GCP, and AWS. -Experience with Kubernetes and container orchestration. -Experience with event-driven frameworks/platforms and high-volume data processing. -Extensive experience with Generative AI (GenAI) and Machine Learning solution design and implementation. -Experience building complex agentic workflows and automation solutions. -Experience with financial data processing and analytics enabled by AI/ML. -Experience building semantic layers using RAG, Knowledge Graph, and GraphRAG technologies. -Experience enabling NLP-based querying against large, complex relational databases. -Experience with analytics AI use cases such as forecasting, fraud detection, and prediction using ML.

Job Description

The Finance Technology AI Enablement team is seeking a Senior Lead AI Developer who can work independently and partner directly with business leaders and subject matter experts (SMEs) to understand current business processes and design AI-driven solutions that transform how those processes operate. This role requires a hands-on technical leader who is equally comfortable architecting complex, distributed AI/ML systems and presenting solutions and roadmaps to business and IT leadership.

Key Responsibilities

-Work independently and collaborate directly with business leaders and SMEs to understand current business processes, pain points, and objectives. -Design and propose AI-enabled solutions that transform and automate existing business processes end-to-end. -Create automation, AI, and ML architecture, including detailed technical design, and lead the build-out of the resulting solutions. -Design and implement Generative AI, Machine Learning, automation, and complex agentic workflow solutions. -Build high-performing, complex semantic layers using advanced technologies such as RAG, Knowledge Graphs, and GraphRAG. -Enable natural language querying (NLP) against large-volume databases with a large number of tables and complex relationships. -Architect and implement financial data processing and analytics solutions enabled by AI/ML. -Develop analytics AI capabilities, including forecasting, fraud detection, and prediction models using Machine Learning. -Drive an AI-first architecture approach across data processing automation and business process automation initiatives. -Design solutions for high-volume processing using event-driven frameworks and platforms. -Present technical concepts, solution designs, and roadmaps clearly to business leaders and large IT audiences. -Provide technical leadership and mentorship within the AI Enablement team.