AI Engineer

AI Engineer

As an AI Engineer, you will contribute to a multi-year initiative dedicated to advancing our digital-first, AI-powered business for enhanced value and future readiness. In this pivotal role, you will help shape and deliver agentic systems by integrating Large Language Models (LLMs) to orchestrate and automate business workflows, driving operational efficiency and optimizing user experiences. You will be hands-on in solution design, demonstrate engineering excellence, and provide technical leadership across high-impact capabilities, ensuring robust and scalable AI solutions for our organization.

Role Summary:

• Drive the development of the "Agent Ecosystem" by designing, building, and operationalizing enterprise-grade AI agents and the orchestration layer that seamlessly coordinates their interactions.
• Serve as a player-coach, balancing hands-on engineering, building agent prototypes and platform components, with strategic guidance, including shaping product direction, advising on implementation best practices, and fostering a culture of technical excellence.
• Initially focus on creating foundational patterns and frameworks that can be leveraged across the broader agent development landscape, enabling scalability and reusability.

Key Responsibilities:

• Design and implement reliable, scalable data ingestion and integration pipelines for structured, semi-structured, unstructured data (e.g., databases, files, documents, APIs, events), and multi-modal data, ensuring data is AI ready, governed, secure, and observable.
• Experience applying data quality, validation, monitoring and testing frameworks in production pipelines. Ensure pipelines follow enterprise governance, access control, and security standards, including role-based access and lineage considerations. Monitor pipeline performance, troubleshoot failures, and optimize cost and throughput.
• Design and implement an agent orchestration layer (routing, tool-calling patterns, workflow coordination, agent registry integration, state management, and failure/fallback strategies).
• Define and apply enterprise agent patterns (standard agent templates, reusable components, and orchestration controls).
• Establish observability/monitoring for agents and orchestrations: logging, tracing, drift detection signals, agent-specific metrics, and operational dashboards.
• Integrate Microsoft Azure services and Microsoft ecosystem components (with emphasis on Azure AI capabilities and "Foundry" experience where applicable).
• Partner with leadership to clarify expected outcomes/vision and translate them into an executable build plan, architecture decisions, and delivery milestones.
• Operate and support production grade AI solutions to meet availability, reliability, and performance expectation.
• Embed Applied AI Evals considerations into the platform: governance hooks, auditability, risk controls, and operational readiness for agents.

Required Qualifications:

• 5-7 years of AI software engineering experience, with 3+ years in AI/ML engineering, AI agent development, multi-agent systems.
• Deep, hands-on experience across Microsoft Azure services (designing, deploying, and operating cloud-native systems). Certifications in Azure AI Engineer, python is a plus.
• Strong background in AI agent ecosystems (multi-agent patterns, orchestration concepts, agent registries, tool routing, memory/state, evaluation approaches); Experience designing and maintaining CI/CD pipelines using GitHub Actions and CDK for Terraform.
• Demonstrated ability to implement monitoring/observability for AI/agent solutions (logging, tracing, metrics, and operational alerting).
• Proven delivery on multiple AI initiatives—comfortable shaping ambiguity into "the right questions," crisp requirements, and practical design.

Preferred / "Nice to Have":

• Experience with Azure AI Foundry / Microsoft "Foundry" tooling in AI solution enablement and governance/tuning workflows.
• Experience with Applied AI Evals frameworks, agent governance standards, and operational controls in regulated or enterprise environments.
• Familiarity with agent taxonomy/labeling approaches and how to apply them to scale standardized development across teams.
• Background in designing enterprise-grade platform layers (identity, access controls, registry/source-of-truth patterns) for agents.
• Knowledge of Financial Services industry.

Salary: $75,900.00 - $141,900.00

Pay Type: Salaried

The above represents BMO Financial Group's pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.