Jobs in Canada

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Added 5 days ago
M
Senior Machine Learning Engineer / Applied Scientist
Microsoft
Vancouver, BC
- Full-time
Contribute to MLOps (data pipelines, telemetry, regression testing, monitoring).
Added 6 days ago
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Sr Spec, IT
Vale
Canada
- Full-time
We are seeking a Sr. Specialist, AI/Machine Learning Developer to join our AI & Automation Centre of Excellence for a permanent opportunity within Information Technology in Sudbury, ON.…
Added 6 days ago
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Sr AI Engineer
Nutrien
Saskatoon, SK
- Full-time
Implement MLOps and deployment standards - CI/CD for AI, model monitoring, retraining, version and lifecycle management - in partnership with AI Platforms & Operations
Added 6 days ago
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Sr AI Engineer
Nutrien
Calgary, AB
- Full-time
Implement MLOps and deployment standards - CI/CD for AI, model monitoring, retraining, version and lifecycle management - in partnership with AI Platforms & Operations
Added 6 days ago
S
AI Risk Management & AI Risk Engineering Consultant
Slalom
Toronto, ON · Greater Toronto Area, Canada
- Full-time
· MLOps or LLMOps experience, including CI/CD for models and agents, model and prompt registries, versioned rollout and production monitoring.
Added 6 days ago
AC
Manager, Data and AI - AI Systems Integrations and Agentic technical owner
Air Canada
Toronto, ON · Dorval, QC
- Full-time
Drive approved infrastructure-as-code, CI/CD, MLOps and LLMOps patterns, including application and model promotion, versioning, rollback and environment management.
Added 6 days ago
GT
Business Analyst - Credit Cards Product Analytics & Insight
Global Technical Talent, an Inc. 5000 Company
Toronto, ON
- Contract
Hybrid - Currently one mandatory in-office day per week (Thursday), plus one Friday per month · There is potential for the requirement to increase to two in-office days per week, including a designated squad day
Added 6 days ago
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AI Developer Test Management
Ericsson
Ottawa, ON
- Full-time
…delivery, strengthen software quality, and create a better developer…
Added 6 days ago
D
AWS AI Solution Architect
DEDICATTED
Canada
- Full-time
Understanding of MLOps / LLMOps practices and production AI lifecycle management.
Added 6 days ago
RT
Machine Learning Engineer
Russell Tobin
Toronto, ON
- Contract
…operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI…
Added 6 days ago
VS
Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
…operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI…
Added 6 days ago
ES
Data Architect (Snowflake, DBT & AWS Focused)
Enterprise Solutions Inc.
Markham, ON
- Contract
Experience in Designing Streamlit apps and define new capabilities and data products leveraging snowflake ML and MLOPS capabilities
Added 6 days ago
TB
Forward Deployed AI Engineer
Type B Digital
Calgary, AB
- Full-time
Deployment experience on at least one major cloud (Azure, AWS or GCP), plus Docker, CI/CD and basic MLOps or LLMOps.
Added 6 days ago
BC
AI Engineer
BDO Canada
Toronto, ON
- Full-time
Practical experience with DevOps and MLOps practices, including Docker, Kubernetes, and CI/CD pipelines for machine learning workloads.
Added 6 days ago
AI
Senior Forward Deployed AI Engineer (Python, Data & GenAI)
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
Implement MLOps/LLMOps capabilities, including lifecycle management, CI/CD, MLflow, monitoring, deployment automation, rollback, and production support.
Added 7 days ago
B
Senior Databricks Data Platform Engineer
Brillio
Canada
- Contract
…and you will measure your success in platform reliability, developer productivity, and dollars…
Added 7 days ago
VS
Senior Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
…operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI…
Added 7 days ago
AI
Data & Analytics Leader - BFSI, AI Transformation
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
Knowledge of AI, machine learning, Generative AI, Agentic AI, MLOps/LLMOps, responsible AI, and AI-led business transformation.
Added 7 days ago
T
Senior Machine Learning Engineer
TEEMA
Toronto, ON
- Contract
Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, model deployment, monitoring and observability.
Added 7 days ago
CT
Senior ML/AI Engineer, Advanced Analytics & Modelling - Customer Intelligence Platforms
Canadian Tire Corporation
Toronto, ON
- Full-time
Location: Toronto, Ontario (Hybrid: In-office 4 days per week)
Added 7 days ago
Senior AI Platform Engineer
Scotiabank
Toronto, ON
…intersection of software engineering, cloud infrastructure, MLOps, generative AI, and platform engineering, this role provides technical leadership for reusable, secure, and reliable…
Added 7 days ago
B
Data Engineer
Buyerlink
Victoria, BC
- Full-time
Added 7 days ago
AT
Surgical AI Scientist
Adoc Talent Management
Remote, Canada
- Full-time
- Remote
Mode Hybride :3 jours au bureau
Added 7 days ago
QA
Data Engineer II - QuantumBlack, AI by McKinsey
QuantumBlack, AI by McKinsey
Toronto, ON
- Full-time
Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform)
Added 7 days ago
L
Principal AI/ML Engineer
lululemon
Vancouver, BC
- Full-time
…deep expertise in machine learning systems, generative AI, MLOps , and platform architecture to shape company-wide technical strategy and design of the enterprise AI platform and services,…

DEDICATTED

AWS AI Solution Architect

Canada

Full-time

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Job details

Job type: Full-time
Experience: 3+ years of experience in AI/ML, software architecture, solution architecture, or similar technical roles.
Posting language: English
Posted: Nov 5, 2026

Original job description

We are seeking an experienced AWS AI Solution Architect to join our team and work on the design and implementation of production-grade AI and agentic systems. In this role, you will be responsible for defining AI solution architecture, designing multi-agent workflows, and working closely with Software Engineers, Data Engineers, DevOps Engineers, and customer stakeholders to deliver scalable, secure, and reliable AI solutions on AWS.

You will work extensively with Amazon Bedrock, LLM-based applications, agentic frameworks such as LangGraph and LangChain, and modern AWS services used to build and operate enterprise AI platforms.

Engagement: long-term, full-time.

Location: Canada (ON/QC - ideally). !!! Readiness for business trips to Montreal in the nearest time.

What you will be doing:

Design and implement production-grade AI and agentic architectures based on business and technical requirements.
Develop LLM-powered applications, autonomous agents, and multi-agent workflows using frameworks such as LangGraph and LangChain.
Design agent orchestration patterns, including tool usage, routing, planning, memory, state management, human-in-the-loop workflows, and multi-agent collaboration.
Build AI solutions using Amazon Bedrock, including foundation models, Knowledge Bases, Guardrails, model evaluation, and other Bedrock capabilities.
Design and implement RAG architectures, including document ingestion, chunking, embeddings, vector search, retrieval strategies, reranking, and context management.
Integrate AI agents with enterprise systems, APIs, databases, SaaS platforms, and internal tools.
Define architecture for scalable and secure AI workloads across application, data, model, and infrastructure layers.
Participate in hands-on implementation, prototyping, troubleshooting, and technical validation of AI solutions.
Evaluate different foundation models and AI approaches based on quality, latency, scalability, security, and cost requirements.
Establish patterns for observability, tracing, evaluation, testing, and monitoring of LLM and agentic applications.
Define security controls for AI systems, including IAM, data isolation, encryption, PII handling, prompt injection protection, and access control.
Collaborate with Software Engineers, DevOps Engineers, Data Engineers, QA Engineers, and business stakeholders throughout the delivery lifecycle.
Prepare and maintain architecture diagrams, technical documentation, implementation guidelines, and technical decision records.
Support production readiness, performance optimization, troubleshooting, and continuous improvement of deployed AI solutions.

A successful candidate will have:

3+ years of experience in AI/ML, software architecture, solution architecture, or similar technical roles.
Strong hands-on experience designing and implementing LLM-based applications.
Practical experience building AI agents or agentic workflows.
Strong experience with Amazon Bedrock and AWS-based AI architectures.
Experience with agentic and LLM frameworks such as:
LangGraph;
LangChain.
Strong understanding of modern LLM application patterns, including:
Retrieval-Augmented Generation (RAG);
tool/function calling;
agent orchestration;
multi-agent systems;
memory and state management;
structured outputs;
human-in-the-loop workflows.
Strong understanding of prompt engineering and context management.
Experience integrating LLM applications with external APIs, databases, and enterprise systems.
Good understanding of vector databases, embeddings, semantic search, and retrieval techniques.
Strong understanding of cloud architecture principles, including scalability, high availability, security, observability, and cost optimization.
Experience designing APIs and backend services for AI applications.
Understanding of AI application evaluation, including model quality, hallucination reduction, retrieval quality, latency, and cost.
Ability to translate business requirements into practical AI architecture and implementation decisions.
Strong communication skills and the ability to explain complex AI concepts to both technical and non-technical stakeholders.

Will be a plus:

Experience with AWS AgentCore and its capabilities for building and operating AI agents.
Experience with AWS services commonly used in AI platforms, such as:
Lambda/Step Functions;
ECS / EKS;
API Gateway;
DynamoDB;
Aurora / RDS.
Experience with Amazon OpenSearch Service, pgvector, Pinecone, or other vector databases.
Experience implementing MCP-based integrations or similar standardized tool integration approaches.
Experience with LLM observability and evaluation platforms or frameworks.
Experience designing AI solutions that handle sensitive or regulated data.
Understanding of MLOps / LLMOps practices and production AI lifecycle management.
Experience with Python and modern AI application development frameworks.
Experience designing distributed or event-driven architectures.
Experience with additional cloud AI platforms such as Azure AI Foundry or Google Vertex AI.

Working conditions:

16 days of paid time off.
Official public holidays.
Participation in company events.
Health insurance.
Engaging projects with opportunities for career growth.
Certifications, Claude/other tools needed.
Corporate events, team-building activities.
Gifts and recognition from the company.
A friendly, open, and supportive team culture without excessive bureaucracy.

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More about this job

Responsibilities

Design and implement secure, scalable production AI architectures on AWS, including LLM applications, agents, multi-agent workflows, and RAG systems. Integrate AI solutions with enterprise systems, establish evaluation, observability, and security practices, and collaborate with technical teams and stakeholders through delivery and production support.

Requirements

Candidates need at least three years of experience in AI/ML, software or solution architecture, or a similar technical role, with hands-on experience building LLM applications and agentic workflows using Amazon Bedrock, LangGraph, and LangChain. They should understand RAG, cloud architecture, security, APIs, vector search, model evaluation, and be able to translate business needs into practical solutions and communicate effectively with technical and non-technical stakeholders.

Skills

AWS
Amazon Bedrock
AI Solution Architecture
Large Language Models
LangGraph
LangChain
Agentic Workflows
Retrieval-Augmented Generation
Prompt Engineering
Vector Databases
Python
API Design
Cloud Security
LLM Evaluation
Observability
MLOps

Benefits

Paid Time Off
Public Holidays
Health Insurance
Company Events
Career Growth Opportunities
Certifications
Team-Building Activities
Gifts and Recognition

Visa sponsorship

Not detected in the job text

Keywords

AWS
Amazon Bedrock
AWS AgentCore
LangGraph
LangChain
LLM Applications
AI Agents
Multi-Agent Systems
Retrieval-Augmented Generation
Foundation Models
Knowledge Bases
Guardrails
Prompt Engineering
Tool Calling
Human-in-the-Loop
Vector Databases
Embeddings
Semantic Search
Python
MCP
Lambda
Step Functions
ECS
EKS
API Gateway
DynamoDB
Aurora
OpenSearch
LLMOps
Distributed Architectures

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Work requirements

Jobs in Canada