Senior AI Engineer, Finance AI & Automation

Bank N.A.; Chicago (IL); On-site; USD 150,000 - 210,000; Full time

Job summary

BMO is hiring a Senior AI Engineer to design, build and run production-grade AI solutions across Finance. You will own solutions end to end, including user experience, APIs, and agentic workflows, with strong emphasis on governance and auditability.

You will partner with FP&A, Controllership, Treasury and Finance Ops to translate business problems into scalable AI designs, ensuring reliable, auditable deployments on the enterprise AI platform.

Qualifications

• 7+ years of professional software engineering experience, including 2+ years building and deploying LLM or generative AI applications to production.
• Expert Python, plus 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.
• Experience with cloud AI services, containers, CI/CD and observability tooling.
• Experience in regulated environments with auditability, security and data privacy.
• Ability to communicate technical concepts to non-technical Finance stakeholders and leaders.
• Bachelor's degree in Computer Science, Engineering, Mathematics or related field, or equivalent experience.

Responsibilities

• Design, build and deploy end-to-end AI applications: web front ends (React/TypeScript), backend services and APIs (Python/FastAPI), and integration with Finance data and systems.
• Translate Finance business problems into technical designs, balancing accuracy, latency, cost and maintainability.
• Build evaluation harnesses to measure accuracy, groundedness and regression across model changes.
• Partner with Technology and AI Platform teams on CI/CD, security reviews, resilience and support handover.
• Act as AI Developer under Governance Program: documentation, testing evidence and Monitoring Plans.
• Run demos, build reusable patterns, review code, and mentor analysts and junior engineers.

Skills

7+ yrs exp

LLM production

Python

React/TypeScript

API design

SQL

Data modeling

Agent orchestration

RAG architectures

Vector databases

Cloud AI services

CI/CD

Observability

Security & governance

Stakeholder comms

Education

Bachelor's degree in CS/Engineering/Math

Tools

Databricks

Snowflake

Power BI

Oracle

Hyperion

GitHub Copilot

MCP servers

Job description

Application Deadline:

11/29/2026

Address:

320 S Canal Street

Job Family Group:

Data Analytics & Reporting

BMO is hiring a Senior AI Engineer to design, build and run production-grade AI solutions across Finance. You will own solutions end to end:

• user experience and APIs
• agentic workflows
• retrieval and data integration
• evaluation and ongoing monitoring

You will build on BMO's enterprise AI platform and within the Finance AI Governance Program. Your work will be safe and auditable, and it will hold up to regulatory review.

You will partner directly with leaders in FP&A, Controllership, Treasury and Finance Operations. Typical use cases include:

• variance analysis and commentary
• reconciliations and manual journal entries
• close acceleration
• controllership and policy research
• treasury forecasting

This role is for engineers who have shipped AI to production, not only built prototypes.

Why join

Shape how AI changes Finance at one of North America's largest banks, working with senior Finance leadership.

Build real solutions that go to production, on an enterprise AI platform designed for scale and governance.

Help set engineering and Responsible AI standards for the Finance AI function.

Key accountabilities

Solution engineering

• Design, build and deploy end-to-end AI applications: web front ends (React/TypeScript), backend services and APIs (Python/FastAPI), and integration with Finance data and systems.
• Translate Finance business problems into technical designs, and make sound trade-offs between accuracy, latency, cost and maintainability.

Agentic AI and LLM systems

• Build multi-step agentic workflows using tool and function calling, MCP integrations, and orchestration frameworks.
• Design retrieval-augmented generation (RAG) over Finance policies, documents and structured data, including chunking, embeddings, vector search and context engineering.
• Embed human-in-the-loop controls for material judgments, approvals and financial postings.

Evaluation and quality

• Build evaluation harnesses with golden datasets to measure accuracy, consistency, groundedness and regression across model and prompt changes.
• Document methodology, assumptions and limitations. Define acceptance thresholds with business owners.

Production readiness and operations

• Partner with the Technology and AI Platform teams on CI/CD, security reviews, resilience and support handover.
• Use the shared enterprise platform services (AI gateway, guardrails, registry, observability) rather than building parallel tooling.
• Instrument tracing, usage, cost and drift monitoring. Respond to and resolve production issues.

Governance, risk and data controls

• Act as the AI Developer under the Risk and Finance AI Governance Program: complete use case documentation, testing evidence and Ongoing Monitoring Plans address conditions raised in 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.

Adoption and leadership

• Run demos and pilots, gather feedback, and track adoption and value-realization metrics.
• Build reusable patterns, components and templates that speed up future Finance AI use cases.
• Review code, set engineering standards, and mentor analysts and junior engineers.

Qualifications

Required

• 7+ years of professional software engineering experience, including 2+ years building and deploying LLM or generative AI applications to production.
• Expert Python, plus 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 (e.g., LangGraph, Semantic Kernel, AutoGen or equivalent) RAG architectures and vector databases 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.

Preferred

• Finance domain knowledge: 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.

Researches, builds, and implements scalable artificial intelligence systems capable of learning and making predictio