B
Senior AI Engineer, Finance AI & Automation
BMO
3 hours ago
Full-time
On-site
Chicago, Illinois, United States
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. " #J-18808-Ljbffr
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. " #J-18808-Ljbffr