AI Solution Architect

BMO • Covina, CA

3d • $120,000 - $250,000 • Remote

About The Position

BMO North American Commercial Bank is building AI capabilities to deliver intelligent, scalable solutions that improve client service, decision-making, and complex banking processes. The AI Solution Architect works with business, product, data, AI, and technology leaders to design end-to-end AI solutions for Commercial Banking use cases, with an emphasis on agentic AI, machine learning, and intelligent workflow automation.

The role translates complex banking processes and user journeys into scalable solution architectures, defining how AI agents, machine-learning models, data services, applications, and human interactions work together. It provides architecture leadership throughout the solution lifecycle, from business problem definition and design through development, integration, deployment, and production readiness. This includes defining agent responsibilities and interactions, orchestration patterns, data and knowledge requirements, model and tool integration, human-in-the-loop controls, system interfaces, and guardrails.

The architect collaborates with business partners and AI/data science, data engineering, software engineering, architecture, security, risk, and platform teams to deliver solutions that are technically sound, scalable, reusable, secure, and aligned with enterprise architecture and governance standards. The role leads solution design for AI initiatives, guides technical teams, evaluates technology choices and trade-offs, supports consistency across agentic journeys, and helps establish reusable architecture patterns. It also requires keeping current with developments in Generative AI, agentic AI, machine learning, cloud platforms, and enterprise AI architecture.

Requirements

• 10+ years of relevant experience across financial services, AI/ML, solution architecture, data, or software engineering.
• Strong experience designing end-to-end enterprise AI solution architectures, including integration across business applications, data platforms, APIs, AI/ML services, and cloud technologies.
• Understanding of agentic AI architectures, including multi-agent orchestration, agent/tool interaction, workflow and state management, event-driven patterns, human-in-the-loop design, knowledge retrieval, and AI guardrails.
• Experience translating complex business processes and user journeys into scalable technical and solution architectures.
• Strong understanding of machine learning and Generative AI concepts, including predictive modeling, LLMs, retrieval-augmented generation, embeddings, model evaluation, and the AI/ML lifecycle.
• Proficiency with Python and SQL and ability to work effectively with AI, data science, data engineering, and software engineering teams.
• Experience across the full AI solution lifecycle, including business challenge definition, architecture, development, integration, deployment, monitoring, and ongoing evolution.
• Knowledge of enterprise integration patterns, including APIs, event-driven architectures, messaging, workflow orchestration, and integration with systems of record.
• Experience designing AI solutions with consideration for security, privacy, responsible AI, model risk, resiliency, observability, and enterprise controls.
• Strong business stakeholder engagement skills and ability to communicate complex architecture concepts to technical and non-technical audiences.
• Ability to lead solution design across multidisciplinary teams and provide technical direction and mentorship to architects, engineers, data scientists, and AI practitioners.
• Ability to balance business value, user experience, technical feasibility, risk, cost, scalability, and time-to-market in architecture decisions.
• Advanced degree in a relevant field such as computer science, engineering, data science, artificial intelligence, statistics, mathematics, or a related discipline.

Nice To Haves

• Financial services experience; Commercial Banking domain knowledge is a strong asset, including familiarity with lending, underwriting, credit, onboarding, relationship management, treasury, and payments.
• Knowledge of cloud platforms such as AWS or Azure, Generative AI platforms, and modern AI/ML development technologies.

Responsibilities

• Design end-to-end AI solution architectures for Commercial Banking use cases, particularly agentic AI journeys, machine learning, and intelligent workflow automation.
• Translate complex business processes and user journeys into scalable technical architectures by understanding users, decisions, data, systems, controls, and handoffs.
• Define agent responsibilities and interactions, orchestration patterns, data and knowledge requirements, model and tool integration, human-in-the-loop controls, system interfaces, and guardrails.
• Provide architecture leadership across the AI solution lifecycle, from business problem definition and design through development, integration, deployment, and production readiness.
• Collaborate with business, AI/data science, data engineering, software engineering, architecture, security, risk, and platform teams.
• Lead solution design for one or more AI initiatives and guide technical teams through architecture and implementation decisions.
• Evaluate technology choices and trade-offs and promote consistency across multiple agentic journeys.
• Establish reusable architectural patterns to accelerate delivery across Commercial Banking.
• Keep abreast of developments in Generative AI, agentic AI, machine learning, cloud platforms, and enterprise AI architecture.

Benefits

• Health insurance
• Tuition reimbursement
• Accident insurance
• Life insurance
• Retirement savings plans
• Performance-based incentives may be included
• Discretionary bonuses may be included
• Other perks and rewards may be included
• Training and coaching
• Manager support and network-building opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior