Jobs in Canada

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Added 27 days ago
C
Data Engineering Expert
Co-operators
Burlington, ON
- Full-time
Work Model: Hybrid (2 days in office)
Added 27 days ago
C
Data Engineering Expert
Co-operators
Guelph, ON
- Full-time
Work Model: Hybrid (2 days in office)
Added 27 days ago
KG
Kafka Platform Engineer/Admin
K&K Global Talent Solutions INC.
ON · Ontario, Canada
- Full-time
Collaborate with application, data engineering, infrastructure, and DevOps teams to onboard and support Kafka applications.
Added 27 days ago
KG
Senior Python Developer (PySpark & AWS Platform Engineering)
K&K Global Talent Solutions INC.
ON · Ontario, Canada
- Contract
We are seeking an elite Senior Python Developer with a mastery of PySpark and AWS distributed infrastructure to drive the engineering and integration of our core data platform ecosystem.…
Added 27 days ago
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Job Posting Title Quantitative Developer, Global Asset Management
BMO
Toronto, ON · FCP
- Full-time
…operations. The ideal candidate combines a deep understanding of data engineering with a strong knowledge of financial markets and…
Added 27 days ago
ZS
Forward Deployed Engineer (Python/PySpark + Claude + SQL + APIs + Data & MLOps)
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Must Have Technical/Functional Skills
Added 27 days ago
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Senior Software Engineer
PointClickCare
Mississauga, ON
- $142,000 to $158,000 CAD / year
- Full-time
Knowledge of scripting languages such as Python, Bash or Groovy
Added 27 days ago
B
Job Posting Title Quantitative Developer, Global Asset Management
BMO
Toronto, ON
- Full-time
…operations. The ideal candidate combines a deep understanding of data engineering with a strong knowledge of financial markets and…
Added 27 days ago
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Senior AI Machine Learning Engineer
SAP
Montreal, QC
- Full-time
…This role sits at the intersection of research and systems engineering and will help shape the next generation of relational foundation model for structured…
Added 27 days ago
AS
Applied Scientist, Alexa Connections
Amazon Science
Vancouver, BC
- Full-time
Master's degree or above in computer science, electrical engineering, or related field
Added 27 days ago
MR
Data Analyst IV
Motion Recruitment
Toronto, ON
- Contract
A leading Canadian financial institution is hiring a Senior Data Analyst / Product Owner for a hybrid, long-term contract role in Toronto, ON. The work is mostly Power BI, SQL, Python and…
Added 27 days ago
MC
AI Platform Engineer (35577)
Myticas Consulting
Toronto, ON
- Contract
Degree in Computer Science, Engineering, or a related field.
Added 27 days ago
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Application Developer
Hays
ON · Ontario, Canada
- $70 to $75 CAD / hour
- Contract
Seeking a Senior Software Engineer with experience in software development, cloud engineering, DevOps, and data platforms. The role involves building enterprise applications and APIs,…
Added 27 days ago
MC
Coherent Optical Systems Engineer (35886)
Myticas Consulting
Ottawa, ON · Kanata, ON
- Full-time
This role requires close collaboration across optical, digital, high-speed analog, ASIC, software, and systems engineering teams. A key aspect of the position is the ability to understand…
Added 27 days ago
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Business Analyst
Dexian
Toronto, ON · Greater Toronto Area, Canada
- Contract
Read, write, and analyze Python and SQL code to support data analysis, validation, and business problem-solving.
Added 27 days ago
R
Senior Software Engineer – Cloud & Data Platforms
Raise
Toronto, ON
- Contract
Work Arrangement: Hybrid, onsite 2 days per week (3 days optional)
Added 27 days ago
M
Principal AI Software Engineer
Mphasis
Toronto, ON
- Full-time
5+ years of overall experience in software development, cloud engineering, data engineering, or AI/ML.
Added 27 days ago
TC
Artificial Intelligence Engineer
TMC Canada
Montreal, QC
- Full-time
Technical Stack: Proficiency in Python and experience building APIs, integrations, and enterprise applications; working knowledge of LLMs, prompt engineering, embeddings, vector databases,…
Added 27 days ago
C
AI Inference Core - Infrastructure SW Engineer
Cerebras
Toronto, ON
- Full-time
You will work on Python frameworks, orchestration systems, distributed execution, scheduling, test infrastructure, and developer tooling. You will help define the architecture and APIs that…
Added 27 days ago
MC
Network Engineer (35135)
Myticas Consulting
Ottawa, ON
- Full-time
The Network Service Engineer will work closely with Commercial, Product, Sales Engineering, Customers, Network Engineering, and external contractor teams to provide technical guidance on…
Added 27 days ago
C
Frontier Engineer (Agentic_AI) - Canada
Cognizant
Toronto, ON
- Full-time
Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Engineering, Cyber Security, Mathematics, or a related technical discipline.
Added 27 days ago
C
Frontier Engineer (Agentic_AI) - Canada
Cognizant
Toronto, ON
- Full-time
Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Engineering, Cyber Security, Mathematics, or a related technical discipline.
Added 27 days ago
MC
Senior QA Engineer III – Automation | Banking | API | Kafka | ETL (35729)
Myticas Consulting
Ottawa, ON
- Full-time
This is a senior, hands-on quality engineering role focused on automation framework development, API and backend testing, Kafka/event-driven testing, ETL and data pipeline validation,…
Added 27 days ago
AI
Lead Full Stack with AI
Apptoza Inc.
Toronto, ON
- Contract
You will be responsible for working closely with AI data scientists to support data ingestion and feature engineering, establishing industry best practices, maintaining and managing…
Added 27 days ago
AI
Lead Full Stack with AI
Apptoza Inc.
Toronto, ON
- Contract
You will be responsible for working closely with AI data scientists to support data ingestion and feature engineering, establishing industry best practices, maintaining and managing…

Mphasis

Principal AI Software Engineer

Toronto, ON, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Apr 13, 2027
Posting language: English
Posted: Oct 15, 2026

Original job description

Role Description

Job Title – AI Engineer

We are seeking a hands-on AI Engineer / Generative AI Developer to design, develop, test, and deploy enterprise AI applications on Google Cloud Platform (GCP). The ideal candidate will have practical experience with Gemini Enterprise, Vertex AI, Large Language Models, Retrieval-Augmented Generation, conversational AI, and cloud-native application development.

This role will focus on building AI assistants, enterprise search solutions, RAG applications, and agent-based workflows. The candidate will work closely with AI architects, data engineers, product owners, and business stakeholders to translate functional requirements into secure, scalable, and reliable AI solutions.

Years Of Experience

5+ years of overall experience in software development, cloud engineering, data engineering, or AI/ML.
2+ years of hands-on experience developing AI/ML or Generative AI applications.
Practical experience building applications using GCP, Vertex AI, and Gemini.
Experience implementing RAG, semantic search, conversational AI, or enterprise knowledge-assistant solutions.
Experience working within Agile software development and delivery teams.

Required

Technical Skills:

Generative AI and Gemini

Gemini models and APIs
Gemini Enterprise
Vertex AI and Generative AI Studio
Prompt engineering and prompt management
Function calling and tool integration
Conversational AI and AI assistants
Agentic AI concepts and workflows
Model evaluation, grounding, and response-quality testing

RAG and Enterprise Knowledge Solutions

Retrieval-Augmented Generation
Document ingestion and preprocessing
Chunking, metadata enrichment, and indexing
Embeddings and vector search
Semantic and hybrid search
Retrieval, re-ranking, and grounded response generation
Structured and unstructured enterprise data integration

Google Cloud Platform

Vertex AI
Gemini Enterprise
BigQuery
Cloud Storage
Cloud Run
Cloud Functions
Pub/Sub
Cloud SQL
Vertex AI Vector Search
Basic familiarity with GKE and Dataflow

AI and Application Development

Python
FastAPI
REST APIs
LangChain, LangGraph, or LlamaIndex
JSON and SQL
Git-based development
Unit, integration, and API testing
Logging, monitoring, and application troubleshooting

DevOps and MLOps

CI/CD for AI applications
Cloud Build, GitHub Actions, or equivalent tooling
Containerization using Docker
Vertex AI Pipelines or comparable orchestration tools
Model and prompt versioning
Application monitoring and observability
Basic Infrastructure as Code knowledge, preferably Terraform

Security and Responsible AI

Secure API and application-development practices
Identity and access management
Data privacy and protection
Responsible AI principles
Prompt-injection and sensitive-data handling controls
AI output monitoring and auditability

Preferred Certifications

Google Cloud Associate Cloud Engineer
Google Cloud Professional Machine Learning Engineer
Google Cloud Generative AI certification or skill badge
Google Cloud Professional Cloud Developer
Relevant Python, AI/ML, or cloud-development certification

Key Responsibilities

AI Application Development

Develop and enhance Generative AI applications using Gemini Enterprise, Gemini models, and Vertex AI.
Build AI assistants, chatbots, enterprise search solutions, and agent-enabled workflows.
Develop reusable Python components, APIs, connectors, and integration services.
Integrate AI applications with enterprise systems, data sources, APIs, and business workflows.
Convert business and functional requirements into working application features.

RAG and Knowledge Solutions

Build document ingestion, parsing, chunking, embedding, and indexing pipelines.
Implement semantic search, vector retrieval, re-ranking, and grounded response generation.
Connect AI applications to structured and unstructured enterprise information sources.
Improve retrieval relevance and response quality through testing and tuning.
Support document refresh, metadata management, access control, and knowledge lifecycle processes.

Testing and Evaluation

Create test cases for prompts, retrieval results, model responses, and end-to-end workflows.
Evaluate responses for relevance, groundedness, accuracy, completeness, and consistency.
Identify hallucinations, retrieval gaps, and response-quality issues.
Support regression testing when prompts, models, data sources, or application components change.
Document test results, known limitations, and remediation actions.

Cloud Deployment and Operations

Deploy AI applications using GCP services such as Cloud Run, Cloud Functions, Vertex AI, and GKE.
Support CI/CD pipelines and automated application deployments.
Monitor application performance, errors, latency, usage, and cloud consumption.
Troubleshoot application, integration, data, and deployment issues.
Contribute to performance, scalability, reliability, and cost improvements.

Security and Governance

Follow established enterprise architecture, security, data-governance, and Responsible AI standards.
Implement authentication, authorization, data-protection, and application-logging requirements.
Apply controls for sensitive information, unsafe prompts, model responses, and enterprise data access.
Maintain appropriate technical documentation and evidence required for reviews and audits.
Escalate security, privacy, model-risk, or data-quality concerns to the appropriate leads.

Collaboration and Documentation

Work with AI architects, senior engineers, data engineers, QA teams, product owners, and business analysts.
Participate in technical design discussions, code reviews, sprint planning, demonstrations, and retrospectives.
Prepare technical documentation, configuration guides, API specifications, and operational runbooks.
Provide implementation updates, identify delivery risks, and support issue resolution.
Share reusable components, development practices, and lessons learned with the engineering team.

Preferred Qualifications

Experience implementing enterprise AI assistants or knowledge-search applications using Gemini Enterprise.
Experience integrating Gemini or Vertex AI with business applications and enterprise data sources.
Experience with Vertex AI Vector Search, pgVector, Pinecone, ChromaDB, or FAISS.
Familiarity with BigQuery, Pub/Sub, Cloud SQL, and GCP data services.
Knowledge of GraphRAG, knowledge graphs, or multi-agent patterns is an advantage but not mandatory.
Exposure to MLflow or other experiment and model-tracking tools.
Experience working in a regulated or large-enterprise environment.

Location: Toronto, ON

Work Mode: Hybrid, 3-4 days per week

About Mphasis

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.

Equal Opportunity Employer

Mphasis is an equal opportunity/affirmative action employer. We provide equal employment opportunities to applicants and existing associates and evaluate qualified candidates without regard to race, gender, national origin, ancestry, age, color, religious creed, marital status, genetic information, sexual orientation, gender identity, gender expression, sex (including pregnancy, breast feeding and related medical conditions), mental or physical disability, medical conditions military and veteran status or any other status or condition protected by applicable federal, state, or local laws, governmental regulations and executive orders. View the EEO in the law poster , view the EEO in the law supplement . To view the pay transparency nondiscrimination provision please click and to view the E-Verify posting click .

Mphasis is committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of disability to search and apply for a career opportunity, please send an email to accomodationrequest@mphasis.com and let us know your contact information and the nature of your request.

Apply on LinkedIn About employer

More about this job

Responsibilities

Develop and deploy enterprise AI applications, assistants, search solutions, and agent workflows using Gemini, Vertex AI, and GCP. Build and evaluate RAG pipelines, integrate enterprise data and systems, and support secure, reliable operations through testing, monitoring, documentation, and collaboration.

Requirements

Requires 5+ years of overall software, cloud, data, or AI/ML experience, including 2+ years developing AI/ML or generative AI applications. Candidates should have hands-on experience with GCP, Vertex AI, Gemini, RAG or related enterprise AI solutions, Python, and Agile delivery; relevant cloud or AI certifications are preferred.

Skills

Generative AI
Gemini
Vertex AI
Retrieval-Augmented Generation
Python
Google Cloud Platform
Prompt Engineering
Conversational AI
Semantic Search
Vector Search
FastAPI
LangChain
CI/CD
Docker
Responsible AI
Cloud Deployment

Visa sponsorship

Not detected in the job text

Keywords

Gemini Enterprise
Gemini Models And APIs
Vertex AI
Generative AI Studio
Retrieval-Augmented Generation
Google Cloud Platform
BigQuery
Cloud Storage
Cloud Run
Cloud Functions
Pub/Sub
Cloud SQL
Vertex AI Vector Search
Python
FastAPI
REST APIs
LangChain
LangGraph
LlamaIndex
Prompt Engineering
Function Calling
Semantic Search
Vector Search
Embeddings
Docker
CI/CD
Cloud Build
GitHub Actions
Terraform
Responsible AI

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Jobs in Canada