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Bank of Montreal seeks an accomplished leader to own the AI platform governance and runtime infrastructure that enables enterprise AI workloads to run securely and compliantly. You will steer a hands‑on team delivering an enterprise‑grade control plane spanning gateway, policy engine, identity fabric, and observability across clouds.
You will partner with Security, Architecture, DevOps, and domain teams to scale the platform, ensure regulatory defensibility, and drive evidence generation for
Application Deadline: 10/29/2026 Address: 320 S Canal Street Job Family Group: Technology Director, Enterprise AI Platform Engineering
BMO is building a dedicated AI Engineering function to deliver the platform capabilities that make enterprise AI safe, governed, and scalable across our business domains and regulatory regimes. We are seeking an experienced technical leader to own the core infrastructure that governs and enforces how AI runs at BMO - the AI Gateway, Policy Engine, Identity Fabric, AI Registry, Guardrails Runtime, and AI Observability. This is a build-and-run leadership role. You will lead a team that designs, ships, and operates the control and orchestration infrastructure sitting between policy authoring and inline enforcement — the capabilities every AI workload at BMO consumes to be secure, compliant, and observable. You will not own the AI models or applications themselves (those are domain-owned); you own the governed platform they run on, and the runtime evidence that proves they run within policy. You are a hands‑on technical leader who has built platform capabilities at scale, operates what you build, and designs for operability and regulatory defensibility from day one.
You blend deep engineering credibility with the executive presence to partner across Security, Architecture, DevOps, and domain teams. You are energized by taking real engineering assets — an existing developer portal, AI registry, a body of policy-as-code, and gateway integrations — and formalizing, scaling, and governing them into an enterprise‑grade platform.
A production‑hardened Developer Portal and federated AI Registry with sub‑5‑day self‑service onboarding. An AI Gateway operational in a selected business domain, meeting tiered latency targets. Policy‑as‑code infrastructure distributing domain‑scoped policy bundles via GitOps, with a working simulation sandbox. A runtime evidence pipeline producing lineage‑stamped, audit‑ready traces aligned to model‑risk and regulatory expectations. A team scaled from an initial core (8–12FTE) toward steady‑state through a blend of net‑new hiring and reallocation of experienced internal engineers.
Build‑run integrated – your team operates what it builds; there is no separate run team. You design for operability and Engineering support from the start. Federated – you own the enforcement infrastructure domains consume; domains own their workloads. You enable, you don’t centralize execution. Evidence‑first – regulatory evidence (e.g., OSFIE‑23, OCC model‑risk expectations) is produced at runtime through instrumented infrastructure, not assembled retroactively. Capability‑aligned – your teams own outcomes (“Identity Fabric works across all platforms”), not specific technologies.
8+ years in technical platform, infrastructure, or AI/ML engineering roles in a large enterprise, including 4+ years leading and managing engineering teams. Proven organizational leadership: building and scaling engineering teams from a small core to steady‑state, including workforce planning, hiring, succession planning, and structuring squads for clear ownership and accountability. Demonstrated team building across blended teams — integrating net‑new hires with reallocated and seconded internal engineers into a single high‑performing team with shared identity and standards. Strong mentoring and coaching track record: developing engineers and technical leads, growing depth and bench strength, giving effective performance feedback, and creating clear technical growth pathways. Ability to establish and sustain a healthy, inclusive team culture that promotes psychological safety, mutual respect, recognition, and employee engagement, aligned to BMO Values. Experience leading through change and ambiguity — standing up a new function, aligning a team to a fast‑evolving mandate, and maintaining momentum under tight timelines. Conflict resolution and cross‑team influence, including partnering with peer Directors on shared roadmaps and resolving competing priorities.
Demonstrated experience building and operating platform capabilities at scale — API gateways, policy/authorization systems, identity/workload‑identity infrastructure, observability pipelines, or equivalent shared services. Strong knowledge of GenAI platform engineering: LLM/AI gateways, model routing and abstraction, RAG and agentic patterns, guardrails, and AI evaluation approaches. Hands‑on experience with policy‑as‑code and authorization systems (Cedar, OPA/Rego, or equivalent) and GitOps‑based distribution. Experience with workload identity and zero‑trust patterns (SPIFFE/SPIRE, mTLS, token exchange, federated identity) — or strong adjacent identity/security engineering depth. Strong observability engineering background: OpenTelemetry, distributed tracing, and telemetry pipelines across operational, security, and compliance domains. Multi‑cloud fluency (AWS and Azure preferred), cloud‑native architecture, containerization/Kubernetes, and Infrastructure as Code. Hands‑on familiarity with modern AI/ML tooling (e.g., Bedrock, Azure OpenAI, SageMaker, Databricks, MLflow, LangChain, or equivalents) sufficient to lead technical direction. Proven CI/CD, DevSecOps, and MLOps/LLMOps delivery experience. Governance, Strategy & Communication Solid grounding in Responsible AI, AI/data governance, privacy, and — ideally — model‑risk management and financial‑services regulatory expectations. Executive‑grade communication and relationship management across technical and senior‑leadership audiences (written, verbal, and presentation). Strategic and organizational management skills, including multi‑year roadmap planning, budgeting, forecasting, and vendor engagement in partnership with Vendor Management. A critical thinker with strong analytical, problem‑solving, and prioritization abilities across a complex, multi‑stakeholder portfolio.
Solid grounding in Responsible AI, AI/data governance, privacy, and — ideally — model‑risk management and financial‑services regulatory expectations. Executive‑grade communication and relationship management across technical and senior‑leadership audiences (written, verbal, and presentation). Strategic and organizational management skills, including multi‑year roadmap planning, budgeting, forecasting, and vendor engagement in partnership with Vendor Management. A critical thinker with strong analytical, problem‑solving, and prioritization abilities across a complex, multi‑stakeholder portfolio.
Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline (Master’s preferred). Relevant certifications an asset: cloud (AWS/Azure/GCP) architecture or ML/AI certifications, Kubernetes (CKA/CKAD), security/identity certifications, or enterprise architecture (TOGAF or equivalent).
Salary: $150,700.00 - $261,800.00 Pay Type: 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.
To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards
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 http://jobs.bmo.com/us/en
BMO is proud to be an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristics. We also consider applicants with criminal histories, consistent with applicable federal, state and local law. BMO is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e‑mail to BMOCareers.Support@bmo.com and let us know the nature of your request and your contact information.
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BMO is a leading bank driven by a single purpose: to Boldly Grow the Good in business and life. Everywhere we do business, we’re focused on building, investing and transforming how we work to drive performance and continue growing the good.