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Generative Ai Developer Jobs in Ontario (NOW HIRING)

You will develop and scale Generative AI-powered systems, including large language model (LLM ... The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities ...

ML/AI Engineer

Toronto, ON · On-site +1

CA$110K - CA$150K/yr

The ML / AI Engineer design, build, deploy, and operate production-grade machine learning and generative AI systems. This role owns the end-to-end ML lifecycle, ensuring models and AI services are ...

Service Now AI DevOps Engineer

Mississauga, ON · On-site +1

CA$99K - CA$132K/yr

Experience with Generative AI, Agentic AI, AI Agents, and AI workflow orchestration. * Experience ... Experience with cloud-native architectures, CI/CD, automated testing, and DevOps practices.

Service Now AI DevOps Engineer

Mississauga, ON · On-site +1

CA$99K - CA$132K/yr

Experience with Generative AI, Agentic AI, AI Agents, and AI workflow orchestration. * Experience ... Experience with cloud-native architectures, CI/CD, automated testing, and DevOps practices.

... and generative AI applications using enterprise AI development platforms, large language models, and low-code automation and app-building tools * Apply techniques such as prompt engineering ...

AI Full Stack Developer

Ottawa, ON · On-site

CA$114K - CA$171K/yr

Design, develop, and implement Generative AI agents to enhance user experience and automate processes. * Work closely with designers, product owners, and other developers to produce top-quality ...

AI Full Stack Developer

Toronto, ON · On-site

CA$114K - CA$171K/yr

Design, develop, and implement Generative AI agents to enhance user experience and automate processes. * Work closely with designers, product owners, and other developers to produce top-quality ...

You will design and implement AI/ML and Generative AI solutions, operationalize them through robust engineering practices, and help shape how OMERS leverages AI to deliver measurable business ...

RQ11252 - Sr. AI Engineer

Toronto, ON · On-site

CA$90.18 - CA$108.22/hr

RQ11252 - Sr. AI Engineer 11-month contract (226 business days) - possible extension ONSITE 5 days ... Hands-on experience implementing Generative AI and Large Language Model (LLM) solutions in ...

The role has a strong focus on generative AI, agentic AI and modern software engineering , while contributing to reusable Applied AI foundations that can be scaled across multiple business use cases.

AVP, AI

Toronto, ON · Hybrid

CA$152K - CA$283K/yr

... Generative AI, and Agentic AI solutions - all while meeting enterprise standards for security ... Conduct full-stack AI engineering work, including hands-on development, prototyping, and ...

You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems. You are fluently able to leverage the latest Generative AI systems and ...

Showing results 41-60

Generative Ai Developer information

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What are popular job titles related to Generative Ai Developer jobs in Ontario?

For Generative Ai Developer jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Generative Ai Developer jobs in Ontario look for?

The top searched job categories for Generative Ai Developer jobs in Ontario are:

Infographic showing various Generative Ai Developer job openings in Ontario as of August 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Vice President, AI Engineer

Toronto, ON • On-site

BMO Capital Markets
1 - 5K employees

Full-time

Medical, Life, Retirement

Re-posted 10 days ago


Job description

Application Deadline:

Address:

100 King Street West

Job Family Group:

Capital Mrkts Sales & Service, Data Analytics & Reporting

BMO Capital Markets is a leading, full-service financial services provider. We offer corporate and investment banking, treasury management, as well as research and advisory services to clients around the world. #bmocapitalmarkets

About the Role

We are seeking a highly skilled AI Engineer to join the Data Cognition Team (DCT) at BMO Capital Markets. In this role, you will design, develop, and deploy next-generation AI systems with a strong focus on Agentic AI, AI Platforms, AI Harnesses, Generative AI, and Large Language Models (LLMs).

You will work at the intersection of applied AI research and engineering, building scalable, secure, and production-grade AI solutions that enable autonomous workflows, intelligent decision-making, and enterprise-wide AI adoption across Investment Banking and Global Markets. This role is ideal for candidates who are passionate about advancing state-of-the-art AI capabilities and translating cutting-edge research into business value.

Our Team

The Data Cognition Team (DCT) develops and operates a scalable, customizable, and sustainable suite of AI-powered platforms and products that support multiple business units across Capital Markets. We leverage modern AI technologies, including Agentic AI, Generative AI, Retrieval-Augmented Generation (RAG), and multi-agent systems, to solve complex business challenges and drive innovation across Investment Banking, Global Markets, Research, and Corporate Functions.

Key ResponsibilitiesAgentic AI & AI Platform Development
  • Design, develop, and maintain advanced Agentic AI systems, including multi-agent architectures that can reason, plan, collaborate, and execute complex workflows.
  • Build enterprise-grade AI Harnesses and AI Engineering Platforms that support model experimentation, evaluation, deployment, observability, governance, and lifecycle management.
  • Develop autonomous and semi-autonomous AI applications leveraging LLMs, RAG, tool-calling, and workflow orchestration frameworks.
  • Design evaluation frameworks for AI agents, including benchmarking, safety testing, hallucination detection, and performance monitoring.
Architecture & Engineering
  • Architect and deploy scalable AI solutions using microservices, APIs, containers, and cloud-native technologies.
  • Implement distributed compute solutions and optimize large-scale AI workloads for performance, resiliency, and cost efficiency.
  • Design inference pipelines and agent orchestration workflows to reduce latency and improve reliability.
  • Build reusable AI services, SDKs, and components that accelerate enterprise AI adoption.
AI Governance, Security & Observability
  • Apply Responsible AI, model governance, and risk management principles throughout the AI development lifecycle.
  • Implement comprehensive observability, tracing, evaluation, and monitoring capabilities for AI systems and agents.
  • Integrate privacy-preserving techniques, cybersecurity controls, and compliance requirements into AI solution architectures.
  • Establish engineering best practices for secure, production-grade Agentic AI deployments.
Collaboration & Innovation
  • Partner with business stakeholders, product owners, and technology teams to identify opportunities for AI-driven transformation.
  • Contribute to AI strategy, architecture standards, and technology roadmaps.
  • Stay current with emerging AI research, agent frameworks, LLM advancements, and industry best practices.
Qualifications
  • PhD in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Physics, Mathematics, or a related quantitative field with 3+ years of industry experience, OR
  • Master's degree in a related field with 5+ years of industry experience designing and deploying production AI systems.
  • Strong software engineering skills, particularly in Python and modern AI/ML frameworks such as PyTorch and TensorFlow.
  • Extensive experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and advanced prompting techniques.
  • Hands-on experience building Agentic AI systems, including planning, memory, tool usage, workflow orchestration, and multi-agent collaboration.
  • Experience with AI orchestration frameworks such as LangGraph, CrewAI, AutoGen, BeeAI, Semantic Kernel, LangChain, or similar technologies.
  • Experience developing AI Harnesses, evaluation frameworks, model benchmarking solutions, and AI observability platforms.
  • Strong understanding of distributed computing, microservices architecture, APIs, Docker, Kubernetes, and cloud-native development.
  • Experience implementing production-grade AI governance, monitoring, security, and Responsible AI practices.
  • Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
  • Research publications, patents, or demonstrated contributions in AI, machine learning, Agentic AI, or LLM-related domains.
  • Experience with vector databases and knowledge platforms such as Milvus, Weaviate, Pinecone, OpenSearch, or Azure AI Search.
  • Experience with AI observability and evaluation platforms such as Langfuse, Arize, Weights & Biases, MLflow, Phoenix, or similar tools.
  • Knowledge of reinforcement learning, reasoning systems, multi-agent coordination, and AI planning techniques.
  • Experience building enterprise AI platforms supporting hundreds or thousands of users.
  • Experience working within regulated industries such as financial services.
Nice to Have
  • Knowledge of Capital Markets, Investment Banking, Trading, Research, and Financial Data domains.
  • Experience with Responsible AI, Model Risk Management, and AI Governance frameworks.
  • Certifications in AI engineering, machine learning, cloud platforms (AWS, Azure, GCP), or cybersecurity.
  • Experience contributing to open-source AI projects or internal AI platform initiatives.

Base Salary: $120,000-$150,000 CAD

(subject to negotiation and subject to the candidate meeting the specific skills, experience, education, and qualification requirements)

Salary:

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.