Senior AI Engineer for Observability

Description

Application Deadline:

11/29/2026

Address:

33 Dundas Street West

Job Family Group:

Data Analytics & Reporting

Hybrid role

Designs, builds, and maintains systems that track, evaluate, and debug non-deterministic AI models and agent workflows. Trace LLM calls, monitor token usage, detect drift, set up automated evaluations, and govern autonomous agent behaviors in production.

Designs and develops machine learning (ML) and deep learning systems.

Runs machine learning tests and experiments. Trains and retrain systems to prevent drift and optimize results.

Solves complex problems with multi-layered data sets, extends existing ML frameworks and optimizes existing machine learning libraries.

Develops Machine Learning apps, implements algorithms, and builds tools to apply ML frameworks.

Turns unstructured data into useful information by auto-tagging images and text-to-speech conversions.

Develops ML algorithms to analyze huge volumes of historical data to make predictions.

Runs tests, performs statistical analysis, and interprets test results.

Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.

Provides specialized consulting, analytical and technical support.

Exercises judgment to identify, diagnose, and solve problems within given rules.

Works independently and regularly handles non-routine situations.

Broader work or accountabilities may be assigned as needed.

Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en .

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Requirements

• Bachelor's Degree in Computer Science, Engineering or other relevant domain
• 7-10 years experience in Site Reliability Engineering
• Experience in Artificial Intelligence Observability Engineering, facilitating the ability to Automate Detect, Investigate, and Remediate
• Exposure to Platform Engineering, building AI capabilities
• Highly proficient in automation, monitoring, observability, buildouts, AI engineering, understand model architectures, evaluation metrics, token usage, and how to spot concept or data drift
• Experience using Python for custom evaluations and SQL or LogQL/PromQL for querying telemetry, logs, and metrics data.
• Provision, configure, and standardize observability pipelines, logging sidecars, and centralized dashboards using Prometheus, Grafana, Datadog) to track SLIs/SLOs, handle alert fatigue, and run root cause analysis.
• Exposure to heavily regulated industry organizations
• Agent & LLM Tracing: Implement OpenTelemetry-based frameworks to capture step-by-step agent trajectories, spans, prompts, tool calls, and intermediate outputs.
• Evaluation & Quality Assurance: Design automated evaluation pipelines for relevance, groundedness, hallucination detection, and prompt adherence using LLM-as-a-judge or custom code.
• Drift & Performance Monitoring: Track model drift, data quality degradation, latency spikes, and error rates across production pipelines.
• Cost & Token Optimization: Build telemetry and sampling strategies to control high data and inference costs, managing log retention and cardinality.
• Agent Governance & Guardrails: Define operational boundaries for autonomous AI agents, setting rules for when they can self-remediate.
• Alert Hygiene & Incident Response: Reduce alert fatigue by replacing static thresholds with dynamic, intelligent anomaly detection and building runbooks for AI failures.

Conditions

$80,000.00 - $175,000.00

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. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards