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Generative Ai Developer Jobs in Ontario (NOW HIRING)

CA$105K - CA$125K/yr

Oversee deployment of AI/ML, Generative AI, Intelligent Automation, and Advanced Analytics solutions. * Partner with Data Science, Data Engineering, Cloud Engineering, Security, and Architecture ...

Develop and optimize prompts using Generative AI prompt engineering techniques to support enterprise AI solutions. * Build and integrate APIs and backend services that enable AI-powered applications.

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 ...

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 ...

Manager - Azure AI Engineering

Toronto, ON · Hybrid

CA$84K - CA$175K/yr

Enough about us, let's talk about you Required skills: • 6-10+ years in data, AI, or software engineering • Proven experience delivering AI/ML or Generative AI solutions • Hands-on experience ...

Sr. GenAI Engineer

Toronto, ON · Hybrid

CA$130K - CA$145K/yr

... & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and ... Embed Generative AI Tools:Integrate cutting-edge Generative AI frameworks into current Capital ...

As a Senior AI Engineer on the ASEDA team , you'll be building the agentic AI and generative AI systems that are transforming how the enterprise operates. Think AI agents that can reason, plan, use ...

As a Staff Engineer on the ASEDA team , you'll be at the center of RBC's most ambitious AI bet - building the agentic AI and generative AI systems that are transforming how the enterprise operates.

We are a growing science and engineering team with an exciting charter and need your passion ... As a part of our team, you will bring deep expertise in Generative AI and quantitative modeling ...

Showing results 41-60

Generative Ai Developer information

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 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 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.

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 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 80% Full Time, 17% Part Time, and 3% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution.

Senior Developer, AI Engineering

Scotiabank

Toronto, ON • Hybrid

Full-time

PTO

Re-posted 3 days ago


Job description

Requisition ID: 257097 
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

The Senior AI Engineer is a senior technical individual contributor responsible for designing, building, and operationalizing enterprise grade AI solutions in a highly regulated banking environment. This role provides deep technical leadership across AI engineering, MLOps/LLMOps, and governance by design, ensuring AI solutions are secure, scalable, auditable, and production ready.

You will own complex AI systems end to end, influence platform standards, and act as a technical authority for AI delivery-bridging experimentation and enterprise production while meeting strict risk, privacy, and regulatory expectations.

 

Is this role right for you? In this role, you will:

  • Act as a technical lead for AI engineering initiatives, owning design decisions for complex, highimpact AI solutions.
  • Define and contribute to reference architectures, reusable patterns, and "golden paths" for AI development and deployment across the bank.
  • Review and approve AI solution designs to ensure alignment with platform standards, security controls, and governance requirements.
  • Design and implement productiongrade AI services and pipelines (batch and realtime) with strong focus on reliability, performance, and operational excellence in the cloud
  • Lead the packaging and deployment of models as scalable services (APIs, jobs, agents) with clear SLAs, monitoring, alerting, and runbooks.
  • Own complex problem resolution across environments, including production incidents related to AI systems.
  • Embed AI governance directly into engineering workflows, including:
    • Security and access controls
    • Data classification and handling
    • Model risk management requirements
    • Privacy and consent controls
    • Responsible AI principles
    • Auditability and regulatory traceability
  • Partner closely with Risk, Compliance, Legal, and Architecture teams to ensure AI solutions meet internal and external regulatory expectations.
  • Lead implementation of Generative AI patterns such as RetrievalAugmented Generation (RAG), embeddings, semantic search, and agent workflows.
  • Ensure GenAI solutions are grounded in approved data sources, governed access, logging, and retention policies.
  • Define evaluation and monitoring approaches for GenAI outputs in regulated use cases.
  • Design and implement automated ML/LLM delivery pipelines covering training, evaluation, approval, deployment, and rollback.
  • Establish standards for model versioning, reproducibility, environment isolation, and controlled releases.
  • Reduce timetoproduction while increasing safety, repeatability, and governance through automation.
  • Mentor senior and midlevel engineers, raising the overall technical bar across AI engineering
  • Contribute to internal standards, documentation, and knowledge sharing.

 

Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have:

  • Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
  • 8+ years of experience in cloud engineering, with 5+ years focused on AI/ML systems
  • Expertlevel proficiency in Python, SQL and cloud infrastructure
  • Handson experience deploying AI solutions in cloud environments (Azure and GCP).
  • Deep understanding of production concerns: reliability, scalability, observability, cost, and security.
  • Experience delivering AI solutions in regulated industries (banking, financial services, insurance, healthcare).
  • Strong familiarity with model risk management, audit requirements, and regulatory review processes.
  • Handson experience with enterprise MLOps / LLMOps tooling and platform design.
  • Experience designing platformlevel AI capabilities, not just individual models.

 

What's in it for you?

  • Diversity, Equity, Inclusion & Allyship - We strive to create an inclusive culture where every employee is empowered to reach their fullest potential, respected for who they are, and are embraced through bias-free practices and inclusive values across Scotiabank. We embrace diversity and provide opportunities for all employee to learn, grow & participate through our various Employee Resource Groups (ERGs) that span across diverse gender identities, ethnicity, race, age, ability & veterans.
  • Accessibility and Workplace Accommodations - We value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. Scotiabank continues to locate, remove and prevent barriers so that we can build a diverse and inclusive environment while meeting accessibility requirements.  
  • Upskilling through online courses, cross-functional development opportunities, and tuition assistance. 
  • Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.
  • Dynamic Ecosystem - Free tea & coffee, universal washrooms, and lots of space for team collaboration.
  • Community Engagement - No matter where you choose to work from; we offer opportunities for community engagement & belonging with our various programs.

#AIDataPlatforms

Location(s):  Canada : Ontario : Toronto 
Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.  
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our  Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.