Principal Architect

Job summary

Define end-to-end platform architecture for data ingestion, APIs, workflows, integrations, and deployment, including scalable systems for large physical datasets and distributed edge environments. Set technical roadmaps and production standards, guide architectural decisions, and mentor engineers as the team builds its Physical AI platform.

Job details

Location: Kitchener, ON, Hybrid, 3 days on-site per week Language: Strong written and spoken English communication skills Employment Type: Permanent, Full-Time Compensation: $140,000-$180,000 base salary, plus 10% bonus, with potential flexibility About the Opportunity Join a global industrial technology organization as a Principal Platform Architect, helping build a new Physical AI platform and robotics engineering capability from the ground up. You’ll work at the intersection of AI, robotics, industrial systems and large-scale data, creating the platform foundations that turn intelligent software into real-world actions. As a senior technical leader on an initial team of approximately 14 technical professionals, you’ll partner closely with the Team Lead, AI/ML and robotics specialists, software engineers and DevOps professionals. This is a fast-moving environment where you’ll bring a production mindset to emerging technology, helping the team move from early concepts and pilots to scalable industrial applications. What’s In It for You You’ll have the opportunity to shape the architecture, technical roadmap and engineering practices of a new strategic initiative rather than inherit an established platform. You’ll gain exposure to cutting-edge Physical AI, robotics, edge computing and AI/ML technologies while mentoring a growing technical team and collaborating with global research, product and engineering groups. Your Responsibilities - You’ll define end-to-end platform architecture spanning data ingestion, APIs, metadata, workflow execution, connectors and deployment foundations. - You’ll design scalable data contracts, service boundaries, event-driven services and integration patterns for robot, vision and edge systems. - You’ll architect platforms capable of managing terabyte-scale physical data, including validation, governance and dataset versioning. - You’ll create technical roadmaps and guide cloud, storage, security, observability and production-hardening decisions. - You’ll design distributed and edge-ready solutions that account for geographically dispersed and resource-constrained environments. - You’ll mentor engineers and guide build-versus-partner decisions to keep delivery focused and efficient. Skills and Qualifications - 10+ years of experience in software architecture, platform engineering, backend systems or large-scale distributed applications. - Strong end-to-end platform architecture experience, including cloud-native systems, APIs, event-driven design, security and scalable data platforms. - Strong cloud expertise, preferably AWS, plus scripting experience such as Python. - Experience with AI/ML platforms, MLOps, model evaluation, industrial systems or production AI applications. - Experience with distributed edge applications, DevOps and production product delivery. - Robotics experience, ROS/ROS2, industrial protocols, workflow engines and real-time integration are strong assets. - Strong collaboration, technical mentorship and communication skills, with the ability to turn ambiguity into practical architecture. Note from the Hiring Manager “We’re looking for someone who can bring a production mindset to a brand-new space. You’ll help us make smart architectural decisions, mentor the team and build a platform that can grow with where Physical AI is going.”

What you’ll do

Define end-to-end platform architecture for data ingestion, APIs, workflows, integrations, and deployment, including scalable systems for large physical datasets and distributed edge environments. Set technical roadmaps and production standards, guide architectural decisions, and mentor engineers as the team builds its Physical AI platform.

Requirements

Requires 10+ years of experience in software architecture, platform engineering, backend systems, or large-scale distributed applications, with strong expertise in cloud-native architecture, APIs, event-driven design, security, and scalable data platforms. Experience with AWS, Python, AI/ML platforms, MLOps, edge applications, DevOps, and production delivery is sought; robotics and industrial integration experience are strong assets.

Listed skills

• Amazon Web Services · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Platform Architecture
• Cloud-Native Systems
• AWS
• Python
• Distributed Systems
• Event-Driven Architecture
• API Design
• Scalable Data Platforms
• Data Governance
• AI/ML Platforms
• MLOps
• Edge Computing
• DevOps
• Robotics
• Technical Mentorship

Job areas

• Technology
• Software
• Engineering
• Management & Leadership
• Manufacturing

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