AI Engineer

Posted Yesterday
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Toronto, ON, CAN
In-Office
70K-150K Annually
Senior level
Financial Services
The Role
Design, develop, deploy, and optimize enterprise AI and machine learning solutions, including generative AI, NLP, predictive analytics, RAG systems, AI agents, and LLM applications. Build scalable APIs and services, operationalize models through MLOps and DevOps, establish monitoring and governance, and collaborate with business, data science, engineering, infrastructure, and security teams. Translate business needs into technical solutions, support Agile project delivery, and maintain production AI systems.
Summary Generated by Built In

Application Deadline:

10/29/2026

Address:

33 Dundas Street West

Job Family Group:

Technology

#AIJobsBFUTR


About the Role

We are seeking an innovative AI Engineer to help drive the next generation of intelligent solutions across the enterprise. In this role, you will design, develop, deploy, and optimize AI-powered applications, machine learning solutions, and intelligent automation capabilities that deliver measurable business value. You will partner closely with business stakeholders, data scientists, engineers, and technology leaders to identify opportunities where artificial intelligence can enhance customer experiences, improve operational efficiency, reduce risk, and accelerate decision-making.


The successful candidate combines strong software engineering expertise with practical experience in machine learning, generative AI, automation, and cloud technologies. You are passionate about transforming complex business challenges into scalable AI solutions and thrive in a fast-paced, collaborative environment.


Key Responsibilities:


AI Solution Development

  • Design, build, deploy, and maintain AI and machine learning solutions that address business priorities.
  • Develop and implement Generative AI, Natural Language Processing (NLP), predictive analytics, and intelligent automation use cases.
  • Build scalable AI applications, APIs, and services using modern software engineering practices.
  • Develop proof-of-concepts (POCs), prototypes, and pilot solutions to demonstrate business value and technical feasibility.
  • Integrate AI models into enterprise systems and workflows.

Machine Learning & Generative AI

  • Develop, train, evaluate, and optimize machine learning models.
  • Build and refine Retrieval-Augmented Generation (RAG) solutions, agent-based systems, and LLM-powered applications.
  • Fine-tune and evaluate AI models to improve performance, reliability, and business outcomes.
  • Collaborate with Data Science teams to operationalize models and deploy them into production environments.
  • Monitor model performance and implement ongoing improvements.

Business Partnership & Innovation

  • Partner with stakeholders to understand business challenges and identify AI opportunities.
  • Translate business requirements into technical designs and implementation plans.
  • Facilitate workshops, discovery sessions, and solution design discussions.
  • Create business cases and recommendations for AI investments and initiatives.
  • Stay current on emerging AI technologies, tools, and industry trends.

 

Engineering Excellence

  • Develop high-quality, secure, and maintainable code using enterprise standards.
  • Implement MLOps and DevOps practices to streamline model deployment and lifecycle management.
  • Establish monitoring, testing, governance, and performance frameworks for AI solutions.
  • Collaborate with infrastructure and security teams to ensure scalable and compliant deployments.
  • Contribute to best practices, standards, and reusable AI frameworks.

Project Delivery

  • Participate in Agile delivery environments and contribute to sprint planning, backlog refinement, and execution.
  • Manage project timelines, risks, dependencies, and technical deliverables.
  • Communicate project status, challenges, and recommendations to technical and business stakeholders.
  • Support production deployments and ongoing operational sustainability.

Required Qualifications

  • 3-5+ years of experience in AI Engineering, Machine Learning Engineering, Software Engineering, or a related field.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, Mathematics, or a related discipline.
  • Hands-on experience developing machine learning and AI solutions in enterprise environments.
  • Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, Hugging Face, or similar technologies.
  • Experience building and deploying Generative AI and Large Language Model (LLM) solutions.
  • Strong understanding of machine learning lifecycle management and MLOps practices.
  • Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
  • Experience with API development, data integration, and software engineering best practices.
  • Knowledge of AI governance, security, risk management, and responsible AI principles.
  • Experience working in Agile delivery teams.

 

Preferred

  • Experience with Azure OpenAI, Copilot technologies, AI Agents, or Retrieval-Augmented Generation (RAG) architectures.
  • Experience implementing intelligent automation, process automation, or workflow orchestration solutions.
  • Familiarity with vector databases, knowledge management platforms, and semantic search technologies.
  • Experience in financial services, banking, or other highly regulated industries.
  • Relevant certifications in AI, cloud computing, or machine learning.

Skills & Competencies

  • Strong analytical and problem-solving abilities.
  • Excellent verbal and written communication skills.
  • Ability to influence and collaborate with technical and non-technical stakeholders.
  • Strong execution and project delivery skills.
  • Data-driven decision making.
  • Curiosity, adaptability, and a passion for innovation.
  • Ability to work independently while contributing to a collaborative team environment.

Why Join Us?

You'll have the opportunity to build cutting-edge AI solutions that directly impact customers, employees, and business outcomes. Working alongside technology, data, and business leaders, you'll help shape the future of AI adoption while solving meaningful enterprise-scale challenges. Ready to help define the future of AI? Apply today.

Salary:

$70,000.00 - $150,000.00

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.

Skills Required

  • 3-5+ years of experience in AI Engineering, Machine Learning Engineering, Software Engineering, or a related field
  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, Mathematics, or a related discipline
  • Hands-on experience developing machine learning and AI solutions in enterprise environments
  • Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face
  • Experience building and deploying Generative AI and Large Language Model solutions
  • Strong understanding of machine learning lifecycle management and MLOps practices
  • Experience with cloud platforms such as Azure, AWS, or Google Cloud
  • Experience with API development, data integration, and software engineering best practices
  • Knowledge of AI governance, security, risk management, and responsible AI principles
  • Experience working in Agile delivery teams
  • Experience with Azure OpenAI, Copilot technologies, AI Agents, or Retrieval-Augmented Generation architectures
  • Experience implementing intelligent automation, process automation, or workflow orchestration solutions
  • Familiarity with vector databases, knowledge management platforms, and semantic search technologies
  • Experience in financial services, banking, or other highly regulated industries
  • Relevant certifications in AI, cloud computing, or machine learning

BMO Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about BMO and has not been reviewed or approved by BMO.

  • Parental & Family Support — Paid parental leave up to 16 weeks at full pay for all new parents, plus up to $20,000 for adoption, surrogacy, and fertility, and 10 days of paid backup childcare indicate robust family support. These elements stand out within BMO’s U.S. package.
  • Retirement Support — A 401(k) design combining a core employer contribution with dollar-for-dollar matching up to a set portion of pay, plus immediate vesting on match and employee contributions, signals strong retirement funding. The core contribution’s three-year vesting is clearly defined.
  • Leave & Time Off Breadth — Vacation accrual scales with grade and service, alongside 9–10 paid holidays and additional paid time off buckets (bereavement, school activities, civic duties, blood donation, volunteering). This breadth offers multiple avenues for time away beyond standard vacation.

BMO Insights

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The Company
HQ: Toronto, Ontario
51,885 Employees

What We Do

At BMO, banking is our personal commitment to helping people at every stage of their financial lives. The truth is, people’s needs change: so we change too. But we never change who we are. Which means we’ll never waiver from providing our customers the best possible banking experience in the industry. Our incredible team of over 46,000 people is just the tip of the iceberg. You should get to know us. We’re here to help.

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