Description

Responsibilities

• Work independently and collaborate directly with business leaders and subject matter experts 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.

Qualifications

Required

• More than 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.
• Strong ability to translate business processes into AI/automation architecture and detailed technical designs.
• Ability to work independently with minimal oversight while managing multiple stakeholders.
• Strong analytical and problem-solving skills with an AI-first mindset.
• Excellent communication and presentation skills, with the ability to engage business leaders and large IT audiences effectively.
• Strong collaboration and soft skills, with the ability to build trust with business and technology stakeholders

Key Skills

Education

Bachelor's degree