Senior AI Engineer, Finance AI & Automation

BMO; Chicago (IL); On-site; USD 120,000 - 250,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Job summary

BMO Financial Group seeks a Senior AI Engineer to design, build, and operate production-grade AI solutions for Finance, with governance, safety, and regulatory readiness.

You will develop end-to-end AI applications using React/TypeScript front ends and Python/FastAPI backends, implement RAG pipelines, and integrate with enterprise data, while partnering with risk, finance, and technology teams to deliver scalable, auditable AI capabilities.

Qualifications

• 7+ years of professional software engineering experience, including 2+ years building and deploying LLM or generative AI applications to production.
• Expert Python, and proficiency in a modern front-end framework (React/TypeScript preferred).
• Strong API design, SQL, and data modeling skills.
• Hands-on experience with agent orchestration frameworks, RAG architectures, and vector databases, including prompt and context engineering.
• Experience with cloud AI services (Azure OpenAI / Azure AI Foundry and/or AWS Bedrock), containers, CI/CD, and observability tooling.
• Proven ability to evaluate non-deterministic systems and build automated test and evaluation pipelines.
• Experience in a regulated environment with auditability, explainability, security, and data privacy.
• Ability to communicate technical concepts clearly to non-technical Finance stakeholders and senior leaders.
• Bachelor’s degree in Computer Science, Engineering, Mathematics or a related field, or equivalent experience.
• Finance domain knowledge including financial close, reconciliations, FP&A, treasury, liquidity, or IRRBB.
• Familiarity with model risk management guidance (e.g., OSFI E-23, SR 11-7).
• Experience with Databricks, Snowflake, or Power BI, and with Finance systems such as Oracle or Hyperion.
• Experience building MCP servers or enterprise tool integrations for agents.
• Experience using AI-assisted development tools (e.g., GitHub Copilot) within a governed engineering workflow.
• Bilingual English/French is an asset.

Responsibilities

• Design, build, and deploy end-to-end AI applications, including web front ends using React/TypeScript, backend services and APIs using Python/FastAPI, and integrations with Finance data and systems.
• Convert Finance business problems into technical designs and make trade-offs across accuracy, latency, cost, and maintainability.
• Build multi-step agentic workflows using tool and function calling, MCP integrations, and orchestration frameworks.
• Implement retrieval-augmented generation (RAG) over Finance policies, documents, and structured data, including chunking, embeddings, vector search, and context engineering.
• Include human-in-the-loop controls for material judgments, approvals, and financial postings.
• Create evaluation harnesses using golden datasets to measure accuracy, consistency, groundedness, and regression across model and prompt changes.
• Document methodology, assumptions, and limitations, and define acceptance thresholds with business owners.
• Partner with Technology and AI Platform teams on CI/CD, security reviews, resilience, and support handover.
• Use shared enterprise platform services such as AI gateway, guardrails, registry, and observability rather than creating parallel tooling.
• Instrument tracing, usage, cost, and drift monitoring, and respond to and resolve production issues.
• Act as the AI Developer under the Risk and Finance AI Governance Program, including use case documentation, testing evidence, and Ongoing Monitoring Plans that address conditions from Second Line reviews.
• Apply data classification, access controls, PII protection, and lineage in line with the Data Risk Directive, RDARR principles, and model risk expectations.
• Run demos and pilots, gather feedback, and track adoption and value-realization metrics.
• Build reusable patterns, components, and templates to accelerate future Finance AI use cases.
• Review code, set engineering standards, and mentor analysts and junior engineers.

Skills

Python

React/TypeScript

API design

SQL/data modeling

Agent orchestration

LLM/GAN tech

Cloud AI services

CI/CD/Observability

Governance & Risk

Stakeholder communication

English/French

Education

Bachelor’s degree in CS/Engineering/Math

Tools

LangGraph

Semantic Kernel

AutoGen

Azure OpenAI

Job description

BMO Financial Group is seeking a Senior AI Engineer to design, build, and operate production-grade AI solutions for Finance, from user-facing experiences and APIs to retrieval and agentic workflows. The role focuses on enterprise AI platform development with governance, safety, auditability, and regulatory readiness.

Role Responsibilities

In this position, you will develop end-to-end AI applications that connect Finance business needs with scalable engineering and responsible AI practices.

• Design, build, and deploy end-to-end AI applications, including web front ends using React/TypeScript, backend services and APIs using Python/FastAPI, and integrations with Finance data and systems.
• Convert Finance business problems into technical designs and make trade-offs across accuracy, latency, cost, and maintainability.
• Build multi-step agentic workflows using tool and function calling, MCP integrations, and orchestration frameworks.
• Implement retrieval-augmented generation (RAG) over Finance policies, documents, and structured data, including chunking, embeddings, vector search, and context engineering.
• Include human-in-the-loop controls for material judgments, approvals, and financial postings.
• Create evaluation harnesses using golden datasets to measure accuracy, consistency, groundedness, and regression across model and prompt changes.
• Document methodology, assumptions, and limitations, and define acceptance thresholds with business owners.
• Partner with Technology and AI Platform teams on CI/CD, security reviews, resilience, and support handover.
• Use shared enterprise platform services such as AI gateway, guardrails, registry, and observability rather than creating parallel tooling.
• Instrument tracing, usage, cost, and drift monitoring, and respond to and resolve production issues.
• Act as the AI Developer under the Risk and Finance AI Governance Program, including use case documentation, testing evidence, and Ongoing Monitoring Plans that address conditions from Second Line reviews.
• Apply data classification, access controls, PII protection, and lineage in line with the Data Risk Directive, RDARR principles, and model risk expectations.
• Run demos and pilots, gather feedback, and track adoption and value-realization metrics.
• Build reusable patterns, components, and templates to accelerate future Finance AI use cases.
• Review code, set engineering standards, and mentor analysts and junior engineers.

Required Qualifications

• 7+ years of professional software engineering experience, including 2+ years building and deploying LLM or generative AI applications to production.
• Expert Python, and proficiency in a modern front-end framework (React/TypeScript preferred).
• Strong API design, SQL, and data modeling skills.
• Hands-on experience with agent orchestration frameworks (LangGraph, Semantic Kernel, AutoGen or equivalent), RAG architectures, and vector databases, including prompt and context engineering.
• Experience with cloud AI services (Azure OpenAI / Azure AI Foundry and/or AWS Bedrock), containers, CI/CD, and observability tooling.
• Proven ability to evaluate non-deterministic systems and build automated test and evaluation pipelines.
• Experience in a regulated environment with an understanding of auditability, explainability, security, and data privacy.
• Ability to communicate technical concepts clearly to non-technical Finance stakeholders and senior leaders.
• Bachelor’s degree in Computer Science, Engineering, Mathematics or a related field, or equivalent experience.
• Finance domain knowledge including financial close, reconciliations, FP&A, treasury, liquidity, or IRRBB.
• Familiarity with model risk management guidance (e.g., OSFI E-23, SR 11-7).
• Experience with Databricks, Snowflake, or Power BI, and with Finance systems such as Oracle or Hyperion.
• Experience building MCP servers or enterprise tool integrations for agents.
• Experience using AI-assisted development tools (e.g., GitHub Copilot) within a governed engineering workflow.
• Bilingual English/French is an asset.

Technologies

• React, TypeScript, Python, FastAPI
• MCP integrations, LangGraph, Semantic Kernel, AutoGen
• RAG, vector databases, embeddings, vector search
• Azure OpenAI, Azure AI Foundry, AWS Bedrock
• Containers, CI/CD, observability tooling
• AI gateway, guardrails, registry, tracing
• Databricks, Snowflake, Power BI, Oracle, Hyperion
• GitHub Copilot

Salary and Work Details

• Location: Chicago, IL (onsite)
• Salary: USD 120,000 - 250,000 per yearly
• Pay type: Salaried
• Application deadline: 11/29/2026
• Address: 320 S Canal Street
• Job family group: Data Analytics & Reporting

Benefits

• Health insurance
• Tuition reimbursement
• Accident and life insurance
• Retirement savings plans

Typical Finance AI Use Cases

• Variance analysis and commentary
• Reconciliations and manual journal entries
• Close acceleration
• Controllership and policy research
• Treasury forecasting

About the Opportunity

This role supports scalable development and operation of AI systems across an enterprise platform, aligned to BMO’s Risk Management Framework and risk culture within approved risk appetite. You will contribute to Responsible AI standards for the Finance AI function and deliver production solutions with governance and monitoring built in.

For more details on benefits, visit: https://jobs.bmo.com/global/en/Total-Rewards.

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