Senior AI Solution Architect (Canada)

Jobgether • Canada

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Lead the design, development, and deployment of production-grade AI products and intelligent services across diverse environments. Bridge AI research with secure, scalable, and commercially viable solutions, spanning the full AI lifecycle. Requires deep engineering expertise, product thinking, commercial awareness, and enterprise architecture leadership.

Key Highlights

Lead the complete lifecycle of AI products and intelligent services.

Translate business challenges into scalable AI-powered products and technical roadmaps.

Architect and deploy advanced AI solutions including foundation models, LLMs, VLMs, and agentic AI.

Key Responsibilities

Lead the complete lifecycle of AI products and intelligent services, from opportunity identification and business case development through architecture, development, production deployment, monitoring, and continuous improvement.

Translate business, operational, industrial, IoT, and robotics challenges into scalable AI-powered products, services, and technical roadmaps.

Define solution architectures, data strategies, development approaches, and commercialization plans aligned with business objectives, enterprise architecture, cybersecurity, governance, and operational requirements.

Coordinate multidisciplinary engineering activities to deliver AI solutions on schedule, within budget, and according to established development methodologies and standards.

Design and implement robust data acquisition, labeling, curation, governance, validation, and evaluation strategies.

Develop scalable AI training, fine-tuning, inference, deployment, and MLOps pipelines, including experiment tracking, dataset versioning, model registries, CI/CD, observability, drift detection, and model governance.

Architect and deploy foundation models, LLMs, VLMs, computer vision, multimodal AI, liquid foundation models, sensor intelligence, and robotic perception solutions.

Develop agentic AI systems capable of reasoning, planning, memory, tool use, workflow orchestration, multi-agent collaboration, and human-in-the-loop interaction.

Integrate AI agents with enterprise applications, APIs, knowledge bases, operational systems, industrial equipment, IoT platforms, robotic systems, and edge devices.

Design physical AI and autonomous systems incorporating perception, localization, mapping, planning, manipulation, navigation, motion control, and closed-loop decision-making.

Develop multimodal perception and sensor-fusion solutions using cameras, LiDAR, radar, IMUs, industrial sensors, telemetry, and time-series data.

Build Digital Twin and simulation environments to generate synthetic data, validate AI behavior, test edge cases, evaluate safety, and accelerate training and deployment.

Optimize AI models for edge and resource-constrained environments using quantization, distillation, pruning, LoRA, PEFT, runtime optimization, graph optimization, and hardware-aware techniques.

Deploy real-time AI solutions across cloud, embedded, GPU, NPU, NVIDIA Jetson, industrial edge, robotics, and IoT platforms while balancing latency, throughput, power, memory, and operational cost.

Apply secure-by-design principles and ensure AI solutions meet cybersecurity, privacy, regulatory, governance, resiliency, observability, explainability, and responsible AI requirements.

Define service architectures, operational documentation, deployment guides, runbooks, support models, and technical specifications throughout the AI lifecycle.

Conduct post-implementation reviews and identify opportunities for optimization, automation, monetization, service improvement, and continuous innovation.

Partner with product management, research, engineering, operations, enterprise architecture, cybersecurity, infrastructure, and executive stakeholders to influence AI strategy and accelerate time-to-market.

Communicate complex AI concepts to technical and non-technical audiences and provide strategic recommendations, assessments, dashboards, and technical roadmaps.

Mentor engineering teams, establish technical standards and best practices, and promote continuous improvement across AI development and service delivery.

Ensure AI initiatives create measurable client and business value while maintaining high standards for operational excellence, service quality, security, and profitability.

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Technical Skills Required

Python PyTorch Machine Learning

Benefits & Perks

Competitive annual compensation range of CAD $95,000–$145,000

Fully remote working opportunity within Canada

Opportunity to work on advanced AI initiatives

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Nice to Have

Ph.D. is an asset.

Certifications such as ITIL, Scaled Agile, Kubernetes, AWS, Azure, Google Cloud, NVIDIA, or related technologies are beneficial.

Experience in industrial automation, manufacturing, logistics, transportation, aerospace, energy, utilities, healthcare, or other mission-critical environments is an asset.

Experience with embodied AI, world models, synthetic data, simulation-driven AI, safety-critical systems, open-source AI or robotics, publications, patents, or recognized technical innovation is desirable.

Job Description

As a Senior AI Solution Architect, you will lead the design, development, deployment, and evolution of production-grade AI products and intelligent services.You will bridge advanced AI research with secure, scalable, commercially viable solutions across enterprise, cloud, edge, IoT, robotics, and industrial environments.The role spans the full AI lifecycle, from opportunity identification and business case development through architecture, model development, MLOps, deployment, and optimization.You will work with cutting-edge technologies including foundation models, LLMs, VLMs, multimodal AI, agentic AI, computer vision, robotics, and physical AI.

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