The role involves building customer-facing features from scratch using strong frontend skills while integrating and scaling the underlying AI infrastructure. This includes owning features end-to-end, crafting reliable software, and applying applied AI knowledge beyond the API layer to ensure system reliability.
Remote AI Engineer Jobs in Canada (141)
Search = AI Engineer
Remote in = Canada
The role involves implementing automated MLOps pipelines, including CI/CD, data, and training processes, alongside implementing ETL pipelines for data ingestion. Responsibilities also include containerizing and deploying models, continuous monitoring for drift, and managing model and data versioning.
Develop and maintain end-to-end data pipelines and participate in building Samsara’s Data Platform. Manage critical data pipelines and facilitate data integration and transformation requirements.
Design and implement AI-powered features and integrate LLMs into Vanta's existing products to accelerate customer compliance. Collaborate with cross-functional teams to build scalable AI systems, establish guardrails, and mentor other engineers.
Design and operate scalable cloud services for connected hardware, focusing on telemetry ingest and real-time state management. Lead cross-functional initiatives and integrate AI-native engineering practices into the development lifecycle.
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Design and optimize prompt-based AI models and low-code solutions using Microsoft Power Platform to improve supply chain efficiency. Collaborate with stakeholders to gather requirements and implement automated workflows to streamline business operations.
Design and optimize prompt-based AI models and low-code solutions using Microsoft Power Platform to improve supply chain efficiency. Collaborate with stakeholders to gather requirements and build automated workflows to streamline business operations.
Own the end-to-end development of AI-powered product experiences from ambiguity through launch. Collaborate with cross-functional teams to build reliable, fast, and user-centric software across the full stack.
Design and integrate AI workflows using agentic architectures and orchestration frameworks into customer-facing products. Build and scale fullstack web application features, APIs, and cloud services while mentoring other engineers.
Senior Software Engineer, AI Platform & Agents
Coalition, Inc.
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Full Time
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6 Days Ago
Coalition, Inc.
Lead the development of an internal AI platform and orchestration components to accelerate the deployment of AI Agents and RAG pipelines. Build scalable SDKs and APIs that bridge the gap between LLM capabilities and production-grade applications.
Build the application-layer foundations and shared architecture for AI integration across the Roofr platform. Design scalable integrations with third-party APIs and maintain rigorous evaluation frameworks for AI system accuracy.
Design and manage scalable data platforms for real-time and batch processing using AI-assisted development workflows. Own the full data lifecycle from ingestion via Kafka and Kinesis to delivering modeled datasets in a Databricks Lakehouse.
Design and operate AI-powered services and internal tools to improve developer and operator productivity. Partner with cross-functional teams to implement secure, scalable LLM integrations and track success via productivity metrics.
The role involves architecting and implementing scientific and ML software to bridge the gap between R&D prototypes and production-ready tools. Responsibilities include managing the full software lifecycle, integrating modules into the simulation platform, and collaborating with domain experts.
The Senior AI Engineer will design and deploy autonomous agents to automate development processes and build complex AI-driven workflows within patient and provider portals. They will also ensure the cloud architecture is scalable and reproducible.
Lead the end-to-end machine learning lifecycle to design and deploy AI-first SaaS products using Large Quantitative Models. This includes building robust data pipelines, developing novel ML algorithms, and collaborating with cross-functional teams to create real-world MVPs.
Senior AI Engineer - Grafana Ops, AI/ML | Canada | Remote
Grafana Labs
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Full Time
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1 Week Ago
Grafana Labs
Develop and scale high-performance AI features and agentic workflows to help users detect and resolve incidents using observability data. Collaborate with cross-functional teams to prototype, test, and ship AI-powered automation tools for infrastructure quality.
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Design, build, and deploy AI-powered applications including chatbots and enterprise copilots on the Azure platform. Implement multi-LLM orchestration and RAG workflows while managing CI/CD pipelines and MLOps.
Design and implement an autonomous learning system and RL loop to improve trading agent strategies based on live outcomes. Own the model and inference infrastructure, including the build-vs-buy decisions for model hosting and optimization.
Design, build, and deploy AI-powered applications including chatbots and enterprise copilots on Azure. Implement multi-LLM orchestration and RAG workflows while managing CI/CD pipelines and performance monitoring.
Security Software Engineer, AI & Automation - Canada
NerdWallet
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Full Time
·
2 Weeks Ago
NerdWallet
Design and build AI-powered security systems and multi-agent LLM architectures to automate threat modeling and vulnerability analysis. Partner with engineering teams to integrate security guidance into workflows and enhance the secure software development lifecycle.
Design and build core components of an AI agent platform, including orchestration layers and tool integrations. Architect knowledge and memory infrastructure while implementing trust, safety, and evaluation frameworks for AI-driven operations.
Design and build core components of an AI agent platform, including orchestration layers and tool integrations. Architect knowledge infrastructure and implement trust and safety frameworks for AI-driven operations.
Develop and maintain backend services and AI-native platforms using Python, Node.js, and AWS serverless architectures. Collaborate with cross-functional teams to build scalable, integration-heavy platforms and improve system reliability.
Build and own full-stack AI features, including multi-step pipelines, financial document ingestion, and output evaluation frameworks. Develop backend infrastructure and API layers to transform crypto activity into auditable financial records.
Design and implement Temporal AI SDK features and integrations across various frameworks and libraries. Take end-to-end ownership of features while collaborating with the developer community and providing technical documentation.
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Lead the design and development of production-grade AI agentic systems and RAG pipelines to automate client tasks. Establish AI engineering standards and architect scalable backend services and data pipelines on AWS.
Design, implement, and deploy end-to-end production AI/ML systems, including data pipelines and training workflows. Collaborate with cross-functional teams to integrate AI agents into enterprise operations and maintain system reliability.
Rapidly transform rough ideas and sketches into clickable iOS prototypes and native surfaces like Live Activities and Dynamic Island. Collaborate directly with founders and designers to iterate on AI-powered features and orchestrate AI agents for code generation and testing.
Design and scale asynchronous APIs and multi-agent AI workflows using Python and Semantic Kernel. Implement RAG systems and integrate various LLM providers while maintaining robust CI/CD pipelines and observability.
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