Senior AI & Automation Specialist (Hybrid)

Key Responsibilities

• Leads the design and architecture of enterprise AI solutions, integrating machine learning, NLP, and cognitive services into automation platforms.
• Defines scalable frameworks and standards for AI-enabled automation, ensuring alignment with enterprise architecture and governance requirements.
• Evaluates, selects, and implements AI technologies, tools, and vendors in accordance with risk appetite, regulatory expectations, and enterprise standards.
• Drives end-to-end delivery of intelligent automation use cases, including alert triage, document intelligence, predictive exception handling, and decision support.
• PARTNERS cross-functionally with Technology, Data Science, Operations, Risk, and Compliance to operationalize AI solutions in production environments.
• Establishes best practices for AI model integration, orchestration with RPA platforms (e.g., UiPath), and cloud-based AI services.
• Safeguards all AI solutions meet model risk management, data governance, and regulatory compliance requirements.
• Provides technical leadership and mentorship to automation team members, elevating AI literacy and solution design capabilities.
• Translates business needs into scalable AI-enabled solutions with measurable operational and financial outcomes.
• Supports automation pipeline governance through solution evaluation, feasibility assessment, and prioritization activities.
• Drives continuous improvement of enterprise automation capabilities, introducing innovative AI applications aligned with strategic objectives.
• Contributes to broader program activities including cross-functional coordination, governance support, analysis of processes and systems, and preparation of materials for decision-making forums, as needed.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience).
• Combined experience in AI, machine learning, intelligent automation, or advanced analytics.
• Demonstrated experience designing and deploying AI/ML solutions in enterprise or regulated environments.
• Proven ability to lead complex, cross-functional technology initiatives.
• Experience integrating AI capabilities into operational workflows and automation platforms.
• Strong understanding of model risk, data governance, and regulatory considerations within financial services.