Senior AI Engineer, Finance AI & Automation

BMO Financial Group is building production-grade AI capabilities for Finance, with an enterprise approach that emphasizes governance, safety, auditability, and regulatory readiness. This onsite role in Chicago, IL focuses on end-to-end delivery, from user experience and APIs to agentic workflows, retrieval, evaluation, and monitoring, all using shared AI platform services.

What you’ll do

• Design, build, and deploy end-to-end AI applications spanning web front ends (React/TypeScript), backend services and APIs (Python/FastAPI), and integration with Finance data and systems.
• Convert Finance business problems into technical designs, making 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.
• Apply 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 (AI gateway, guardrails, registry, observability) rather than building parallel tooling.
• Instrument tracing, usage, cost, and drift monitoring, and respond to production issues.
• Act as the AI Developer under the Risk and Finance AI Governance Program, completing required use case documentation, testing evidence, and Ongoing Monitoring Plans addressing 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, collect feedback, and track adoption and value-realization metrics.
• Develop reusable patterns, components, and templates to speed up future Finance AI use cases.
• Review code, set engineering standards, and mentor analysts and junior engineers.

What you bring

• 7+ years of professional software engineering experience, including 2+ years building and deploying LLM or generative AI applications to production.
• Expertise in Python, plus proficiency with a modern front-end framework (React/TypeScript preferred).
• Strong skills in API design, SQL, and data modeling.
• Hands-on experience with agent orchestration frameworks (e.g., LangGraph, Semantic Kernel, AutoGen or equivalent), RAG architectures, vector databases, and 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 understanding of auditability, explainability, security, and data privacy.
• Ability to clearly communicate technical concepts 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: 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.

Salary and location

• Location: Chicago, IL (onsite)
• Salary: USD 120,000 - 250,000 per year
• Pay type: Salaried
• Application deadline: 11/29/2026
• Address: 320 S Canal Street

Benefits

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

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

Typical use cases

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

Job family group: Data Analytics & Reporting