ZipRecruiter

Log In

1

Generative Ai Testing Jobs in Ontario (NOW HIRING)

Source Code

RQ11252 - Sr. AI Engineer

Toronto, ON · On-site

CA$90.18 - CA$108.22/hr

Hands-on experience implementing Generative AI and Large Language Model (LLM) solutions in ... Participates in testing, troubleshooting, deployment and ongoing optimization of AI-powered contact ...

Accenture

AI Full Stack Developer

Toronto, ON

CA$114K - CA$171K/yr

Design, develop, and implement Generative AI agents to enhance user experience and automate ... Establish and uphold coding standards, testing protocols, and quality assurance processes across ...

Accenture

AI Full Stack Developer

Ottawa, ON

CA$114K - CA$171K/yr

Design, develop, and implement Generative AI agents to enhance user experience and automate ... Establish and uphold coding standards, testing protocols, and quality assurance processes across ...

Citi

AI Applied Senior Engineering Lead

Mississauga, ON

CA$145K - CA$217K/yr

This role focuses on implementing scalable, agentic AI frameworks and generative AI solutions ... Strong grounding in modern engineering practices including Git, CI/CD, testing, code reviews, agile ...

Citi

AI Applied Senior Engineering Lead

Mississauga, ON · On-site

CA$145K - CA$217K/yr

This role focuses on implementing scalable, agentic AI frameworks and generative AI solutions ... Strong grounding in modern engineering practices including Git, CI/CD, testing, code reviews, agile ...

Deloitte

AI Solutions Architect

Toronto, ON

Generative AI Architecture • Design and deliver end-to-end GenAI solutions from concept through ... Testing, monitoring, evaluation frameworks • Establish patterns for prompt management, model ...

Autodesk

Promote CI/CD, automated quality checks, contract testing, and developer tooling to increase ... Experience working with or alongside ML/AI or research teams to productionize capabilities, and ...

Vangard, Inc.

Senior AI Scientist

Toronto, ON · On-site

Design and execute adversarial evaluations of generative AI and agentic systems, probing for safety ... testing, and the ability to identify confounds and methodological flaws in existing analyses

HollisWealth

AI Enablement Specialist

Toronto, ON · On-site

Run user acceptance testing before rollout, and adjust solutions based on what testing shows ... Stay current on developments in generative AI and the Canadian regulatory environment, and apply ...

Td

Applied Machine Learning Scientist II

Toronto, ON

CA$125K - CA$154K/yr

Experience developing, evaluating, and deploying machine learning and Generative AI solutions. Strong understanding of model evaluation methodologies, experimentation, statistical testing, and ...

BrokerLink

AI Developer I

Oakville, ON · On-site

Develop solutions using Generative AI, Large Language Models (LLMs), Retrieval Augmented Generation ... Experience supporting solutions through testing, deployment, operational support, and continuous ...

BrokerLink

AI Developer I

Toronto, ON · On-site

Develop solutions using Generative AI, Large Language Models (LLMs), Retrieval Augmented Generation ... Experience supporting solutions through testing, deployment, operational support, and continuous ...

previous pagenext page

Showing results 21-40

All JobsGenerative Ai Testing JobsGenerative Ai Testing Jobs in Ontario

Generative Ai Testing information

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

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

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

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

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

What cities in Ontario are hiring for Generative Ai Testing jobs?

Cities in Ontario with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Ontario as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution.

RQ11252 - Sr. AI Engineer

Source Code

Toronto, ON • On-site

CA$90.18 - CA$108.22/hr

Contractor

Re-posted 27 days ago

Job description

RQ11252 - Sr. AI Engineer

11-month contract (226 business days) - possible extension

ONSITE 5 days - 222 Jarvis St

Must Have:

  • 5+ years of experience developing Artificial Intelligence and Machine Learning solutions.
  • Hands-on experience implementing Generative AI and Large Language Model (LLM) solutions in enterprise environments.
  • 5+ years of experience implementing contact centre solutions utilizing Amazon Connect.
  • Experience configuring and developing Amazon Connect Customer AI Agents.
  • Extensive experience designing, developing and implementing Amazon Connect cloud-based contact centre solutions.
  • Experience integrating Amazon Bedrock services with Amazon Connect solutions.
  • Experience designing, developing and optimizing prompts for conversational AI, virtual assistants and AI agents.
  • Experience with AWS services including Amazon Connect, Amazon Bedrock, Amazon Lex, AWS Lambda, API Gateway, Amazon DynamoDB, Amazon S3, CloudWatch, EventBridge and IAM.
  • Knowledge of Azure OpenAI, Azure AI Services, Azure AI Foundry, Google Vertex AI, Gemini and equivalent AI platforms.
  • Strong experience with Python development.
  • Experience with JavaScript, Node.js and related technologies.
  • 5+ years of experience implementing conversational AI, IVR or contact centre solutions.

Nice to have:

  • Prior OPS or Public sector exp.


Responsibilities:

  • Undertakes the development, configuration, implementation and support of Artificial Intelligence (AI), Generative AI and Conversational AI solutions based on business requirements, architecture standards, security policies, best practices and project deliverables.
  • Designs, develops and supports AI-powered conversational IVR solutions, virtual assistants, voicebots, AI agents and self-service capabilities utilizing Amazon Connect Customer AI Agents, Amazon Bedrock, Amazon Lex and related technologies.
  • Develops and maintains integrations between AI solutions, contact centre platforms, enterprise applications, knowledge repositories, APIs, workflow systems and cloud services.
  • Designs, develops and optimizes prompts, prompt templates, orchestration logic, retrieval mechanisms and AI guardrails to ensure secure, accurate and effective AI interactions.
  • Develops and supports AI Agents leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Model Context Protocol (MCP) servers, tool-calling frameworks and enterprise knowledge repositories.
  • Configures and develops Amazon Lex bots including intents, slots, utterances, fulfillment logic, conversational flows and escalation mechanisms.
  • Works closely with architects, business analysts, contact centre teams and stakeholders to implement scalable, secure and reliable AI solutions.
  • Develops technical specifications, implementation documentation, deployment procedures and operational support materials.
  • Participates in testing, troubleshooting, deployment and ongoing optimization of AI-powered contact centre solutions.
  • Ensures solutions comply with organizational standards for security, privacy, accessibility and Responsible AI.

General Skills:

  • Knowledge of Artificial Intelligence (AI), Generative AI, Machine Learning (ML), Large Language Models (LLMs), Agentic AI and Conversational AI technologies.
  • Knowledge of Retrieval Augmented Generation (RAG), prompt engineering, vector databases and semantic search technologies.
  • Knowledge of Amazon Connect, Amazon Bedrock, Amazon Lex and AWS cloud services.
  • Knowledge of MCP (Model Context Protocol) concepts, tool integration patterns and AI agent orchestration.
  • Knowledge of cloud computing technologies, APIs, microservices and event-driven architectures.
  • Ability to gather technical requirements and translate them into scalable AI solutions.
  • Ability to develop technical designs, implementation specifications and support documentation.
  • Knowledge of technology trends, emerging AI capabilities and industry best practices.
  • Excellent analytical, problem-solving and troubleshooting skills.
  • Excellent verbal and written communication skills, interpersonal skills and teamwork skills.
  • A team player with a track record for meeting deadlines.

AI Disclaimer: Source Code may use artificial intelligence (AI) tools to assist in certain aspects of its recruiting and business operations.

Note: The higher end of the range is intended for absolutely exceptional candidates who meet all must-have requirements and most or all nice-to-have qualifications. The client will evaluate candidates based on both rate expectations and overall skill set when shortlisting.

INCORPORATED RATE RANGE (7.25 billable hours per day)

  • $90.18/hr - $108.22/hr Inc.

T4 RATE RANGE (7.25 billable hours per day)

  • $72.14/hr - $86.58/hr T4