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Added 2 days ago
PR
Senior/Principal LLM & Evals Engineer
Perennial Resources International
Toronto, ON
- Full-time
We are seeking an experienced GenAI engineer with deep expertise in LLM evaluation, production-grade AI systems, and financial services. The successful candidate will design and improve…
Added 2 days ago
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Senior AI Engineer
Chubb
Toronto, ON · Greater Toronto Area, Canada
- Full-time
We are looking for an AI Engineer who has shipped ML and LLM systems, built quality and observability tooling around them in production, and is ready to go deeper on that problem at scale.…
Added 2 days ago
VC
Senior Consultant
Veritas Communications
Lasalle, ON
- Full-time
At Veritas, we don’t just tell stories, we engineer influence. We move at the speed of culture, powered by insight, creativity, and a relentless commitment to earning attention in…
Added 2 days ago
VC
Account Manager
Veritas Communications
Lasalle, ON
- Full-time
At Veritas, we don’t just tell stories, we engineer influence. We move at the speed of culture, powered by insight, creativity, and a relentless commitment to earning attention in…
Added 2 days ago
VC
Account Director
Veritas Communications
Lasalle, ON
- Full-time
At Veritas, we don’t just tell stories, we engineer influence. We move at the speed of culture, powered by insight, creativity, and a relentless commitment to earning attention in…
Added 2 days ago
VC
Senior Account Director
Veritas Communications
Lasalle, ON
- Full-time
At Veritas, we don’t just tell stories, we engineer influence. We move at the speed of culture, powered by insight, creativity, and a relentless commitment to earning attention in…
Added 3 days ago
Senior Agentic AI Software Backend & Platform Engineer
Siemens
Kitchener, ON
We are seeking a Senior Backend & AI Engineer for Siemens Digital Industries Operations Software, to lead the development and scaling of our Agentic AI platform. The role focuses on strong…
Added 3 days ago
Senior Agentic AI DevOps Engineer
Siemens
Kitchener, ON
We are seeking a hands-on Senior DevOps Engineer, to join Digital Industries Operations Software lead the deployment, operation, and scaling of our Agentic AI platform. The role is strongly…
Added 3 days ago
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Technical Program Manager, Forward Deployed Engineering
Baseten
Toronto, ON
- $165,000 to $330,000 USD / year
- Full-time
…OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI…
Added 3 days ago
B
Technical Program Manager, Forward Deployed Engineering
Baseten
Montreal, QC
- $165,000 to $330,000 USD / year
- Full-time
…OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI…
Added 3 days ago
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Sr AI Engineer
Workday
Vancouver, BC · Canada, BC, Vancouver
- Full-time
Agent Factory is where Workday’s next chapter gets built. We’re forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and…
Added 3 days ago
C
Senior Software Engineer, Agent Infrastructure
Cohere
Remote, Canada
- Full-time
- Remote
Turn emerging ML research ideas into production-ready infrastructure
Added 4 days ago
II
Senior Data Engineer
Ipsos in Canada
Vancouver, BC
- Full-time
Ipsos is one of the world's largest research companies and the only one primarily managed by researchers. Ranked the #1 Most Innovative Market Research Supplier by Greenbook’s GRIT report…
Added 4 days ago
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Machine Learning Engineer
EvenUp
Toronto, ON
- $130,000 to $205,000 USD / year
- Full-time
We're looking for a Machine Learning Engineer to join our ML team at EvenUp. You'll develop and deploy models that power Piai™, our proprietary claims-intelligence platform, with a focus on…
Added 4 days ago
Agentic AI Software Backend & Platform Engineer
Siemens
Kitchener, ON
We are seeking a Backend & AI Engineer, for Siemens Digital Industries Operations Software to help build and scale our Agentic AI platform. The role focuses on solid backend engineering,…
Added 4 days ago
Senior Data Engineer
Ipsos
Vancouver, BC
Ipsos is one of the world's largest research companies and the only one primarily managed by researchers. Ranked the #1 Most Innovative Market Research Supplier by Greenbook’s GRIT report…
Added 4 days ago
A
AI LLM Senior Analyst
Accenture
Mississauga, ON · Montreal, QC
- Full-time
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
Added 4 days ago
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Senior AI Engineer
Cloudoplus
ON · Ontario, Canada
- Full-time
We are seeking a highly experienced and technically accomplished Senior AI Engineer with 10+ years of enterprise software engineering, machine learning, artificial intelligence, and…
Added 5 days ago
L
Senior AI/ML Engineer
Limbic
Remote, Canada
- Full-time
- Remote
Senior AI/ML Engineer, remote in Canada: own the AI that assesses patients for US healthcare providers and gets them to the right mental health care faster.
Added 5 days ago
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Senior ML Engineer
Hays
Toronto, ON
- $90 to $100 CAD / hour
- Contract
Senior Machine Learning Engineer – GenAI & Personalisation
Added 5 days ago
Senior Applied AI Engineer - Artificial Intelligence
Bloomberg
Toronto, ON
…over structured data. They bridge the gap between pioneering research and production, building models and agents that answer complex financial questions, write and execute code, and bring…
Added 6 days ago
C
AI Inference Core - Senior SDET, Release Integration Testing
Cerebras
Toronto, ON
- Full-time
We are looking for an experienced, hands-on Senior Software Development Engineer in Test (SDET) to join the Release Integration Testing (RIT) function within Release & Feature Qualification…
Added 9 days ago
M
Senior Data Scientist
Mphasis
Calgary, AB
- Full-time
…work until it runs in their environment. This is a hands-on senior role. You will own problems end to end - scoping with stakeholders, wrangling messy client data, choosing methods that fit…
Added 9 days ago
T
AI / ML Product Engineer
TD
Toronto, ON
- Full-time
We are looking for an AI Platform Product Engineer who can lead AI initiatives from idea to production, and who can teach our engineers to build with AI. This person is technical enough to…
Added 10 days ago
Senior, Software Engineering (AEM + Workfront/Fusion)
DEPT®
Canada
We're looking for a Senior Software Engineer (P2), Workfront + AEM to help our clients' marketing and creative teams get their work done in one place. You'll be the backend developer who…

Cloudoplus

Senior AI Engineer

ON, Canada
Ontario, Canada, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Apr 18, 2027
Posting language: English
Posted: Oct 20, 2026

Original job description

We are seeking a highly experienced and technically accomplished Senior AI Engineer with 10+ years of enterprise software engineering, machine learning, artificial intelligence, and distributed systems experience to architect, design, develop, and deploy highly scalable, production-grade AI platforms.

The ideal candidate will possess deep expertise in Large Language Models (LLMs), Generative AI, Agentic AI, deep learning, transformer architectures, Retrieval-Augmented Generation (RAG), multi-agent orchestration, AI reasoning systems, and cloud-native AI infrastructure.

This position requires extensive hands-on experience developing sophisticated AI applications, optimizing foundation models, implementing autonomous agent workflows, and integrating intelligent systems with complex enterprise platforms.

Key Responsibilities

1. Advanced AI Architecture and Foundation Model Engineering

Architect and implement enterprise-grade artificial intelligence platforms utilizing advanced machine learning algorithms, deep neural networks, transformer architectures, and distributed model-serving infrastructure.

Implement and optimize attention mechanisms, including Multi-Head Attention (MHA), Multi-Query Attention (MQA), Grouped-Query Attention (GQA), FlashAttention, and Rotary Positional Embeddings (RoPE).

Develop custom neural network architectures utilizing PyTorch, TensorFlow, JAX, Hugging Face Transformers, and distributed training frameworks.

Implement advanced model adaptation techniques including supervised fine-tuning (SFT), LoRA, QLoRA, parameter-efficient fine-tuning (PEFT), knowledge distillation, and domain-adaptive training.

Optimize model inference performance using quantization, speculative decoding, KV-cache optimization, continuous batching, tensor parallelism, and pipeline parallelism.

Evaluate and integrate commercial and open-weight foundation models, including GPT, Claude, Gemini, Llama, Qwen, Mistral, and Gemma, based on application requirements, latency, throughput, accuracy, and cost.

2. Generative AI and Advanced LLM Application Development

Design and develop sophisticated Generative AI applications utilizing large language models, multimodal foundation models, and advanced prompt engineering techniques.

Implement structured generation, constrained decoding, function calling, tool execution, and schema-based output validation for reliable enterprise AI applications.

Develop advanced reasoning workflows utilizing planning, decomposition, reflection, self-correction, and iterative verification mechanisms.

Engineer context-management strategies involving semantic compression, dynamic context assembly, prompt caching, and long-context optimization.

Implement enterprise-grade LLM evaluation frameworks to measure factual accuracy, reasoning performance, groundedness, hallucination rates, toxicity, latency, and token utilization.

3. Agentic AI and Autonomous Multi-Agent Systems

Architect and implement advanced Agentic AI platforms capable of autonomous task planning, dynamic decision-making, tool execution, and complex workflow orchestration.

Develop multi-agent systems utilizing LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, and custom Python-based orchestration frameworks.

Design and develop agent memory architectures incorporating short-term conversational memory, persistent long-term memory, semantic memory, episodic memory, and structured state management.

Integrate Model Context Protocol (MCP) clients and servers to securely expose enterprise tools, APIs, databases, and business services to AI agents.

Develop secure agentic transaction workflows utilizing Temporal, Saga orchestration, idempotency, transactional outbox patterns, and compensating transactions..

4. Retrieval-Augmented Generation (RAG) and Enterprise Knowledge Systems

Architect advanced Retrieval-Augmented Generation platforms integrating structured, semi-structured, and unstructured enterprise knowledge sources.

Implement hybrid retrieval architectures combining dense vector embeddings, sparse retrieval, BM25, semantic search, and metadata-based filtering.

Develop multi-stage retrieval pipelines incorporating query rewriting, query decomposition, reranking, contextual retrieval, and relevance optimization.

Design Graph RAG architectures integrating knowledge graphs, graph databases, entity resolution, relationship extraction, and graph traversal.

Implement vector search solutions using Pinecone, Milvus, Weaviate, FAISS, Elasticsearch, OpenSearch, and PostgreSQL with pgvector.

Develop enterprise document intelligence pipelines incorporating document parsing, OCR, semantic chunking, hierarchical indexing, and contextual metadata enrichment.

Implement knowledge ingestion and synchronization pipelines supporting incremental updates, change data capture, data lineage, access controls, and document versioning.

Evaluate retrieval quality using Recall@K, Precision@K, Mean Reciprocal Rank (MRR), NDCG, answer relevance, faithfulness, and citation correctness.

5. Machine Learning, Deep Learning, and Predictive AI

Design and implement advanced supervised, unsupervised, self-supervised, and reinforcement learning solutions for complex enterprise use cases.

Develop predictive modeling pipelines utilizing XGBoost, LightGBM, Random Forest, Support Vector Machines, gradient boosting, and deep neural networks.

Implement distributed model training and experimentation using PyTorch Distributed, DeepSpeed, Ray Train, and distributed data-processing frameworks.

Apply explainable AI methodologies including SHAP, LIME, feature attribution, model interpretability, and model fairness analysis.

Establish rigorous model-validation practices including cross-validation, drift analysis, calibration, robustness testing, and out-of-distribution evaluation.

6. Cloud AI Platforms and Infrastructure Engineering

Design cloud-native AI solutions utilizing Amazon Bedrock, Amazon SageMaker, Azure AI Foundry, Azure Machine Learning, Google Vertex AI, and managed foundation model services.

Implement GPU-accelerated computing environments utilizing NVIDIA CUDA, cuDNN, NCCL, and distributed GPU clusters..ip

Required Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a closely related technical discipline.

10+ years of professional experience in software engineering, distributed systems, data engineering, machine learning, or artificial intelligence, including substantial recent hands-on experience delivering production AI solutions.

Advanced proficiency in Python, object-oriented programming, asynchronous programming, data structures, algorithms, and distributed application development.

Strong experience with PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and modern machine learning frameworks.

Demonstrated expertise in developing Generative AI applications, LLM-powered solutions, RAG architectures, and autonomous agent workflows.

Extensive experience with cloud computing, container orchestration, microservices architecture, distributed messaging, and production AI infrastructure.

Strong understanding of transformer architectures, neural network optimization, vector databases, embedding models, and advanced information retrieval.

Proven ability to design and implement secure, scalable, fault-tolerant enterprise AI systems.

Excellent analytical, architectural, troubleshooting, technical leadership, and communication skills.

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More about this job

Responsibilities

Architect, develop, and deploy scalable enterprise AI platforms and applications, including foundation models, generative AI, autonomous agents, and retrieval-augmented generation systems. Optimize model training and inference, build secure knowledge and data pipelines, and deliver production AI infrastructure across cloud and distributed computing environments.

Requirements

Requires a bachelor's or master's degree in a relevant technical discipline and 10+ years of experience in software engineering, distributed systems, data engineering, machine learning, or artificial intelligence, including recent hands-on production AI work. Candidates should have advanced Python and machine learning framework skills, expertise in LLMs, RAG, and agent workflows, and experience building secure, scalable enterprise systems on cloud infrastructure.

Skills

Python
PyTorch
TensorFlow
Hugging Face Transformers
Generative AI
Large Language Models
Retrieval-Augmented Generation
Agentic AI
Distributed Systems
Machine Learning
Deep Learning
Cloud Computing
Vector Databases
Multi-Agent Orchestration
Model Optimization
Enterprise AI Architecture

Visa sponsorship

Not detected in the job text

Keywords

Python
PyTorch
TensorFlow
JAX
Hugging Face Transformers
Large Language Models
Generative AI
Agentic AI
Retrieval-Augmented Generation
Transformer Architectures
LoRA
QLoRA
Parameter-Efficient Fine-Tuning
LangGraph
LangChain
CrewAI
AutoGen
Semantic Kernel
Model Context Protocol
Pinecone
Milvus
Weaviate
FAISS
PostgreSQL
pgvector
Amazon Bedrock
Amazon SageMaker
Azure AI Foundry
Google Vertex AI
NVIDIA CUDA

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