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Added 1 hour ago
AI-Native Engineering Solutions Sales Specialist
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$150,000 to $165,000 CAD / year
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Développeur.se de logiciels sénior.e - Intégration du jeu et fiabilité de la capture / Senior Software Developer - Game Integration & Capture Reliability
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Electronic Arts (EA)
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Développeur.se de logiciels sénior.e - Plate-forme de capture multimodale / Senior Software Developer - Multimodal Capture Platform
Electronic Arts (EA)
Montreal, QC
Full-time
…of a shared platform for capturing synchronized, multimodal data from EA game engines. You will create the reusable systems that allow title teams and researchers to collect rendering,…
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Développeur.se sénior.e des données d’apprentissage automatique / Senior ML Data Developer
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Added 1 hour ago
Développeur.se de logiciels sénior.e - Intégration du jeu et fiabilité de la capture / Senior Software Developer - Game Integration & Capture Reliability
Electronic Arts (EA)
Montreal, QC
Full-time
As a Senior Software Engineer, you will integrate EA's shared game-data capture technology into production game codebases and establish the systems that make instrumented title builds…
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Directeur.trice technique - Capture de données de jeu / Technical Director - Game Data Capture
Electronic Arts (EA)
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Full-time
As a Technical Director, you will lead the technical strategy for capturing research data from EA game sources. You will define how dedicated title streams, shared instrumentation, capture…
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Agnico Eagle Mines Limited
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Full-time
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The University of British Columbia
Vancouver, BC
$9,599.75 to $14,385.5 CAD / month
Full-time
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CBC/Radio-Canada
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Canada Impact+ Emerging Leader in Translational Quantitative Biomedical Imaging
University of British Columbia
Vancouver, BC · UBCV | Pharmaceutical Sciences Building (PHRM)
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Director, AI Governance and Adoption (T & I) (Telework/Hybrid)
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Added 5 hours ago
Manager, Payroll Operations & Control
University of British Columbia
Vancouver, BC
$9,599.75 to $14,385.5 CAD / month
Full-time
Reporting to the Director, Payroll, the Manager, Control and Operations is a key position for internal controls and governance over the payroll function. This role provides supervisory and…
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BMO

Director, AI Technology Delivery

Toronto, ON, Canada
YNG, Canada

Pay: $140,000.00 - $240,000.00
Apply by: Oct 31, 2026
Experience: 15+ years of progressive experience in technology delivery, engineering, architecture, platform, or product technology leadership, including senior leadership accountability.
Posting language: English
Posted: Sep 23, 2026

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Applications open in a new tab.

Original job description

Application Deadline:

10/30/2026

Address:

250 Yonge Street

Job Family Group:

Data Analytics & Reporting

Hybrid Work Model

About the Role

As Director, Technology Delivery Lead, you are accountable for the end-to-end technology delivery of Em, BMO InvestorLine's premier AI agent. You will lead the integrated delivery system across AI engineering, wealth platforms, Microsoft Azure, data, architecture, quality engineering, cybersecurity, operations, and third parties to deliver safe, resilient, scalable, and measurable client outcomes.

You will operate as the principal technology counterpart to the Product Owner for Em. Together, you are jointly accountable for overall delivery: the Product Owner leads product vision, client value, priorities, and acceptance; the Technology Delivery Lead owns the integrated technology plan, engineering execution, technical quality, production readiness, and predictable delivery. This role is not a program coordination position. It is a hands-on senior technology leadership role with clear decision rights and accountability for outcomes.

Mandate and Decision Rights

Own the integrated technology delivery plan for Em from discovery and architecture through build, evaluation, release, operation, and continuous improvement.
Jointly commit scope, sequencing, release outcomes, and delivery forecasts with the Product Owner, balancing client value, technical feasibility, risk, cost, and capacity.
Make or escalate timely technology delivery decisions across architecture, engineering, environments, data, integration, testing, controls, and production readiness.
Hold delivery teams and partners accountable for agreed outcomes, quality standards, dependencies, and evidence-based release criteria.
Protect the product from unmanaged technical debt, fragmented ownership, late-stage controls, and delivery practices that are not fit for AI.

Key Responsibilities

1. End-to-End Technology Delivery

Lead delivery across multiple cross-functional product and platform teams, establishing one integrated plan, clear critical path, transparent dependencies, and accountable owners.
Convert the product roadmap into executable technology increments, release plans, capacity models, milestones, and outcome-based commitments.
Drive delivery discipline across scope, schedule, cost, quality, resources, risk, and benefits, using forecasts rather than artificial certainty.
Identify constraints early, remove impediments, resolve cross-team trade-offs, and escalate decisions with clear options and recommendations.
Ensure each release has explicit entry, exit, acceptance, operational readiness, and rollback criteria.

2. AI Engineering and AI SDLC Leadership

Apply deep knowledge of generative AI and agentic systems, including LLM orchestration, tool use, retrieval-augmented generation, prompt and context engineering, evaluations, guardrails, memory, and human oversight.
Embed full-lifecycle AI SDLC practices across requirements, design, build, test, evaluation, deployment, monitoring, and model or prompt change management.
Ensure AI quality is measured using fit-for-purpose evaluations covering safety, groundedness, relevance, accuracy, latency, reliability, and client experience.
Champion specification-driven development, automation, reusable engineering patterns, and AI-assisted software delivery where approved.
Ensure deterministic software testing and probabilistic AI evaluation are integrated into CI/CD and release decisions.

3. Azure, Architecture and Platform Integration

Provide senior technical leadership for solutions deployed on Microsoft Azure and integrated with BMO InvestorLine and Wealth Management platforms.
Partner with solution, enterprise, security, data, and platform architects to maintain an approved, scalable target architecture and prevent local optimization or avoidable technical debt.
Ensure APIs, event flows, data services, identity, access, observability, resilience, and non-functional requirements are designed and delivered end to end.
Drive environment readiness, infrastructure as code, automated deployment, telemetry, performance engineering, capacity planning, disaster recovery, and production support readiness.
Promote reuse of enterprise AI capabilities, shared services, patterns, and controls while preserving clear service boundaries and ownership.

4. Advanced Agile and Value-Stream Delivery

Establish and continuously improve an advanced Agile operating model organized around persistent, cross-functional teams and measurable client or business outcomes.
Lead portfolio and product-level planning, backlog readiness, dependency management, release forecasting, and flow optimization across multiple teams.
Use evidence-based metrics such as lead time, cycle time, throughput, work in progress, predictability, escaped defects, reliability, evaluation performance, and value realization.
Reduce handoffs, unnecessary governance, meeting load, and blocked work; create fast decision paths and clear single-point accountability.
Coach delivery leaders, Scrum Masters, engineering leads, and teams in modern product delivery, DevSecOps, continuous delivery, and learning-driven retrospectives.

5. Quality, Risk and Responsible AI

Build quality, privacy, security, regulatory compliance, model risk, accessibility, and responsible AI requirements into delivery from inception, not as release-end checkpoints.
Partner with Legal, Risk, Compliance, Cybersecurity, Privacy, Model Risk, Data Governance, and Technology Risk to establish proportionate controls and auditable evidence.
Ensure full-spectrum observability across application, infrastructure, data, model, prompt, agent, safety, and client-experience performance.
Lead incident response, root-cause analysis, corrective action, and learning reviews for technology or AI quality events.
Maintain transparent risk, issue, dependency, and decision records and ensure material risks are escalated promptly.

6. Stakeholder, Financial and Partner Leadership

Serve as the senior technology delivery voice for Em with InvestorLine, Wealth, Technology & Operations, Applied AI, governance partners, and executive forums.
Provide concise, fact-based reporting on outcomes, delivery confidence, risks, financials, quality, and decisions required.
Own technology delivery financial stewardship, resource planning, vendor performance, commercial dependencies, and delivery commitments.
Lead co-build and vendor engagements with clear accountability, knowledge transfer, architecture compliance, security obligations, and measurable outcomes.
Create an inclusive, high-accountability environment that develops leaders, strengthens technical depth, and keeps teams focused on client outcomes.

Key Success Measures

Predictable delivery of roadmap outcomes and releases, with transparent forecast accuracy and controlled scope change.
Measurable improvement in delivery flow, engineering productivity, automation, quality, and time to value.
AI evaluation thresholds and non-functional requirements met before release and sustained in production.
Stable, secure, resilient production performance with effective observability, incident management, and continuous improvement.
Clear ownership, faster decisions, fewer cross-team handoffs, and effective dependency resolution.
Measurable client adoption, experience, business value, and risk outcomes delivered in partnership with the Product Owner.
Effective financial, capacity, vendor, and technical-debt management.

Required Skills and Competencies

Expert-level technology delivery leadership in large, complex, regulated environments, with accountability for multiple teams and production outcomes.
Deep practical knowledge of AI/ML and generative AI delivery, including agentic architectures, LLM application patterns, evaluations, guardrails, observability, and responsible AI controls.
Strong knowledge of wealth management and digital investing platforms, including client journeys, advice or guidance experiences, market and portfolio data, trading-related integrations, and regulatory considerations.
Advanced proficiency with Microsoft Azure cloud architecture and delivery, cloud-native engineering, APIs, integration, identity and access, data services, telemetry, resilience, and DevSecOps.
Mastery of advanced Agile, product operating models, value-stream management, Lean flow, Scrum or Kanban, portfolio planning, CI/CD, test automation, and evidence-based delivery metrics.
Ability to challenge constructively, make decisions under ambiguity, translate technical complexity into business implications, and influence senior executives.
Commercial and financial acumen, including technology investment, capacity, vendor, contract, and delivery-performance management.
Exceptional leadership, communication, facilitation, negotiation, and talent-development skills.

Qualifications and Experience

15+ years of progressive experience in technology delivery, engineering, architecture, platform, or product technology leadership, including senior leadership accountability.
Demonstrated success delivering enterprise-scale digital products or platforms from strategy through production and ongoing operation.
Demonstrated delivery of AI/ML or generative AI solutions in production, ideally involving multi-agent systems or other complex AI-enabled client experiences.
Significant experience with Microsoft Azure and modern software engineering practices in a regulated enterprise.
Experience in wealth management, brokerage, digital investing, banking, or similarly regulated financial services is strongly preferred.
Proven experience leading cross-functional internal and partner teams through complex dependencies and high-stakes releases.
University degree in Computer Science, Engineering, Information Systems; relevant advanced degree or certifications are considered assets.

Leadership Expectations

Act as an owner: accountable for outcomes, not activity or coordination alone.
Put clients, safety, quality, and sustainable value ahead of pace without evidence.
Create clarity: make responsibilities, decisions, risks, dependencies, and delivery confidence visible.
Lead with technical credibility while empowering engineering and product leaders closest to the work.
Build trust through candour, transparency, inclusion, disciplined follow-through, and continuous learning.

Salary:

$140,000.00 - $240,000.00

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. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

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 https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

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More about this job

Responsibilities

The Director of AI Technology Delivery is responsible for the end-to-end technology delivery of AI agents, leading cross-functional teams across engineering, architecture, and operations. This role involves setting the integrated technology plan, ensuring production readiness, and maintaining high standards for AI quality and performance.

Requirements

Candidates must have 15+ years of progressive experience in technology leadership, with deep expertise in generative AI, Azure cloud platforms, and regulated financial environments. A university degree in Computer Science, Engineering, or Information Systems is required, along with proven success in delivering enterprise-scale digital products.

Skills

AI engineering
Generative AI
Microsoft Azure
Technology delivery
Agile methodology
Wealth management
Cloud architecture
Data analytics
Cybersecurity
Leadership
Strategic planning
Risk management
API integration
DevSecOps
Product management

Benefits

Health insurance
Tuition reimbursement
Accident insurance
Life insurance
Retirement savings plans
Performance-based incentives
Discretionary bonuses

Visa sponsorship

Not detected in the job text

Keywords

AI
Generative AI
LLM
Azure
Cloud-native
Agile
Scrum
Kanban
Wealth Management
Fintech
DevSecOps
API
Data Governance
Machine Learning
Architecture
Infrastructure as Code
Telemetry
Performance Engineering
Risk Management
Compliance
Product Roadmap
Value-stream management
CI/CD
Test automation
Agentic systems
Retrieval-augmented generation
Prompt engineering
Observability
Disaster recovery
Capacity planning

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