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Added 14 days ago
Account Solution Architect
CoreWeave
Toronto, ON
Full-time
Background in ML Engineering, AI Engineering, MLOps, or LLMOps
Added 15 days ago
AI Architect
BrainRidge Consulting
Toronto, ON
$130,000 to $200,000 CAD / year
Full-time
Familiarity with MLOps/LLMOps/AgentOps practices and observability tools such as MLflow, LangSmith, Langfuse, Arize Phoenix, or Weights & Biases.
Added 1 month ago
AI/ML Architect-Accenture Advanced Technology Centers
Accenture
Mississauga, ON · Montreal, QC
Full-time
Run MLOps / LLMOps pipelines for model training, deployment, monitoring, and lifecycle.
Added 11 days ago
Account Executive - Greenfield - Toronto
CoreWeave
Toronto, ON
Background selling AI/ML, MLOps, LLMOps, or adjacent developer tooling alongside infrastructure products
Added 3 days ago
Presales Solutions Architect
Centrilogic
Toronto, ON
Full-time
Presales Solution Architect, Cloud, AI and Data
Added 5 days ago
Architect - Machine Learning
Quantiphi
Canada
Full-time
Experience designing and implementing MLOps/LLMOps pipelines, including model deployment, monitoring, evaluation, versioning, and CI/CD.
Added 11 days ago
Staff Software Engineer
kadence
Toronto, ON
Full-time
Champion MLOps and LLMOps practices across the development lifecycle
Added 14 days ago
Account Executive - Greenfield - Toronto
Weights & Biases
Toronto, ON
Full-time
Background selling AI/ML, MLOps, LLMOps, or adjacent developer tooling alongside infrastructure products
Added 15 days ago
Chief Artificial Intelligence Architect
National Bank of Canada
Montreal, QC
Full-time
Solid knowledge of data platforms, MLOps / LLMOps, and cloud-native AI services such as AWS and Azure.
Added 11 days ago
Principal Architect - AI and Data Platforms
Canadian Tire Corporation
Calgary, AB · Mississauga, ON · Oakville, ON · Toronto, ON
Full-time
As a Principal Architect – AI & Data Platforms, you will play a pivotal leadership role within the Enterprise AI and Emerging Technology team, responsible for shaping and executing the…
Added 19 days ago
Staff Software Engineer, AI
Thomson Reuters
Toronto, ON · Canada, Toronto, Ontario
Full-time
Proven experience with MLOps/LLMOps and managing the complete lifecycle of enterprise AI-powered applications
Added 18 days ago
AI Solutions Architect
SearchLabs
Toronto, ON
$180,000 to $200,000 CAD / year
Full-time
Familiar with MLOps/LLMOps, evaluation frameworks, monitoring, AI security, and responsible AI practices.
Added 6 days ago
Lead Full Stack Developer
UniSysTech Consulting
Toronto, ON · Greater Toronto Area, Canada
Other
CI/CD & MLOps/LLMOps: Establish and refine CI/CD automated deployment pipelines using Infrastructure-as-Code (Terraform, AWS CDK) and support model evaluation/monitoring deployment…
Added 1 month ago
Technical Architect
Mphasis
Toronto, ON
Full-time
We are looking for an experienced MLOPs / LLMOPs Engineer with a strong background in deploying and monitoring machine learning and large language model (LLM) pipelines. The ideal candidate…
Added 2 months ago
Senior Manager - Senior AI Architect
KPMG
Montreal, QC
Full-time
Experience with AI services, data engineering, advanced analytics, MLOps/LLMOps, observability, and cloud security.
Added 25 days ago
Senior Data & AI Architect
SMS Equipment Inc.
Acheson, AB
Full-time
…deployment, monitoring, and continuous improvement through DataOps, MLOps, and…
Added 27 days ago
Principal Architect, AI Platform
BMO
Toronto, ON · BMOPLACE
Full-time
…architectural authority. We are seeking a deeply experienced architect to own architectural coherence for AI across BMO's cloud and workspace estates - spanning AWS, Azure, Microsoft 365,…
Added 27 days ago
Sr Director, Enterprise Data and AI Platform
Dayforce
Canada
Establish enterprise MLOps and LLMOps practices for machine learning and generative AI, including model lifecycle management, prompt and model evaluation, monitoring, observability,…
Added 1 month ago
AI Architect GenAI / Azure AI Foundry & Databricks
J&M Group
Toronto, ON
Full-time
Strong understanding of GenAI Ops (LLMOps/MLOps).
Added 8 days ago
Senior Data Scientist, Commercial
HelloFresh
Toronto, ON
Contribute to the development, implementation, and governance of the global MLOps and LLMOps platforms in Canada.
Added 19 days ago
Senior Software Engineer, AI
Thomson Reuters
Toronto, ON · Canada, Toronto, Ontario
Full-time
Proven experience with MLOps/LLMOps and managing the complete lifecycle of enterprise AI-powered applications
Added 1 month ago
Senior Manager AI Solutions Architecture
Diligent Corporation
Vancouver, BC
Familiarity with MLOps/LLMOps practices (model lifecycle, experiment tracking, evaluation, drift monitoring) and modern engineering practices such as containerization and CI/CD.
Added 27 days ago
Senior Principal Engineer
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
Full-time
…or vLLM, vector-search such as OpenSearch or pgvector, and MLOps/LLMOps practices for evaluation, tracing, versioning, deployment, monitoring, and governance, or equivalent technologies…
Added 17 days ago
AI and Data - Manager - AI Engineer
EY
Toronto, ON
Implement best practices for MLOps, LLMOps, across experimental and production environments, including AI pipeline and microservices deployment into cloud environments, APIs, CI/CD,…
Added 2 months ago
Architecte en IA agentique - Intelligence Engineering / Agentic AI - Sr. Architect - Intelligence Engineering
Slalom
Montreal, Quebec
Full-time
…les tests, le déploiement, l’observabilité et les pratiques MLOps et LLMOps à grande…

BrainRidge Consulting

AI Architect

Toronto, ON, Canada

Pay: $130,000 to $200,000 CAD / year
Job type: Full-time
Apply by: Oct 4, 2026
Experience: 7+ years of experience in software or solutions architecture, including meaningful experience architecting AI or machine learning systems.
Posting language: English
Posted: Sep 4, 2026

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Original job description

BrainRidge Consulting is a premium FinTech Technology Consulting firm with the energy of a startup and the experience of an enterprise. With a mission to empower financial institutions and organizations to thrive in the digital age, we provide cutting-edge technology solutions and strategic guidance to drive innovation and growth. As we continue to grow, we are seeking motivated and experienced AI Architects to join our team.

As an AI Architect, you will design and build enterprise-grade AI solutions, platforms, and agentic systems for our clients. This role sits at the intersection of AI, software architecture, cloud, data, security, and enterprise technology, and you'll work with business and engineering teams to turn complex AI use cases into scalable, secure, production-ready solutions. This role is ideal for someone who goes beyond demos and prompt engineering, with a strong understanding of how to architect AI systems that operate reliably inside large enterprises.

Key Responsibilities

Design end-to-end architectures for Generative AI, Agentic AI, RAG, machine learning, and intelligent automation solutions.
Translate business requirements into scalable technical architectures and implementation approaches.
Architect AI agents, including their tools, workflows, memory, permissions, context, and human-in-the-loop controls.
Design enterprise AI platforms and reusable capabilities, including model gateways and catalogs, agent runtimes and registries, RAG and enterprise knowledge services, prompt and tool registries, and evaluation and observability platforms.
Define guardrails, governance, usage monitoring, and cost controls for enterprise AI systems.
Evaluate and recommend AI models based on capability, latency, security, cost, and use-case requirements.
Design retrieval and knowledge architectures across structured and unstructured enterprise data.
Integrate AI solutions with enterprise applications, APIs, databases, workflows, and systems of record.
Define AI security patterns covering identity, authorization, data protection, prompt injection, tool execution, and agent permissions.
Establish architecture patterns for AI evaluation, observability, testing, monitoring, and production operations.
Define deployment strategies across cloud, hybrid, containerized, serverless, and Kubernetes environments.
Develop reusable AI reference architectures, standards, patterns, accelerators, and architecture decision frameworks.
Lead architecture workshops, technical discovery sessions, and proofs of concept.
Provide technical leadership and guidance to AI engineers, software engineers, data engineers, and platform teams.
Partner with security, data, cloud, enterprise architecture, risk, privacy, and business stakeholders.

Qualifications:

7+ years of experience in software or solutions architecture, including meaningful experience architecting AI or machine learning systems.
Strong experience across generative and agentic AI, including LLMs, RAG, multi-agent systems, tool/function calling, context engineering, AI memory, and model routing.
Experience with AI frameworks such as LangChain/LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or MCP, and model ecosystems such as OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral, or Cohere.
Strong experience with at least one major cloud platform (Azure, AWS, or Google Cloud) and its AI services.
Experience with data and knowledge architecture, including SQL/NoSQL databases, data lakes and warehouses, vector databases, hybrid/semantic search, and knowledge graphs.
Strong understanding of enterprise and software architecture, including distributed systems, microservices, REST APIs, event-driven architecture, Kubernetes, serverless computing, and identity and access management.
Hands-on experience with Python, SQL, APIs, Git, CI/CD, Docker, Kubernetes, and Infrastructure as Code.
Familiarity with MLOps/LLMOps/AgentOps practices and observability tools such as MLflow, LangSmith, Langfuse, Arize Phoenix, or Weights & Biases.
Ability to move comfortably between executive conversations and deep technical discussions.
Demonstrated experience working across multiple business domains and with cross-functional technical and business teams.

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More about this job

Responsibilities

Design and build enterprise-grade AI solutions, platforms, and agentic systems for financial institution clients. Translate complex business requirements into scalable, secure, and production-ready technical architectures.

Requirements

Requires 7+ years of software or solutions architecture experience with a strong focus on generative and agentic AI frameworks. Must be proficient in cloud platforms, data architecture, and hands-on development with Python and Kubernetes.

Skills

AI Architecture
Generative AI
Agentic AI
RAG
LLMs
Cloud Platforms
Python
SQL
Kubernetes
Microservices
Vector Databases
MLOps
Software Architecture
API Design
Distributed Systems
Enterprise Security

Visa sponsorship

Not detected in the job text

Keywords

AI Architect
FinTech
Generative AI
Agentic AI
RAG
LangChain
LangGraph
LlamaIndex
Semantic Kernel
AutoGen
CrewAI
MCP
OpenAI
Anthropic Claude
Google Gemini
Meta Llama
Mistral
Cohere
Azure
AWS
Google Cloud
Vector Databases
Knowledge Graphs
Kubernetes
Docker
CI/CD
MLOps
LLMOps
AgentOps
LangSmith

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