AI/ML Enablement Lead Engineer

Main Responsibilities

• Partner with business and technology teams to identify, evaluate, and prioritize AI use cases.
• Translate business needs into scalable AI solution designs and implementation plans.
• Lead delivery of AI-enabled products and solutions from concept through production.
• Provide technical leadership to engineers, contractors, and delivery teams.
• Guide architecture, design, and implementation decisions related to AI and software engineering.
• Present AI capabilities, demonstrations, and solution recommendations to business and technical stakeholders.
• Collaborate with enterprise AI, architecture, and technology organizations to align initiatives and leverage existing capabilities.
• Influence AI strategy, adoption, and best practices across WCIB.
• Support team growth through mentoring, leadership, and participation in hiring activities.

Must Have Skills

• Strong software engineering background with hands-on application development experience.
• Experience designing, building, or delivering AI-enabled software solutions.
• Experience implementing LLM, RAG, Agentic AI, GenAI, or other modern AI solutions in production environments.
• Experience with AI orchestration and application frameworks such as LangChain, LangGraph, Semantic Kernel, MCP, or similar technologies.
• Experience leveraging Azure OpenAI, OpenAI, Anthropic, Gemini, or comparable enterprise AI platforms.
• Deep understanding of AI solution architecture, prompt engineering, retrieval patterns, model evaluation, and AI application development.
• Experience leading engineers, contractors, or technical delivery teams.
• Strong software architecture and solution design skills.
• Experience translating business needs into technical solutions.
• Excellent communication, presentation, and stakeholder management abilities.
• Proven success delivering complex technology initiatives through cross-functional teams.

Nice to Have Skills

• Banking, financial services, or other highly regulated industry experience.
• Experience supporting corporate banking, commercial banking, capital markets, or wealth management organizations.
• Enterprise AI governance, AI enablement, or AI Center of Excellence experience.
• Experience leading engineering organizations or scaling technical teams.
• Experience influencing technology strategy across large enterprises.
• Experience implementing AI solutions at enterprise scale.
• Experience with cloud-native AI platforms and services on Azure.