Are you an expert in bridging the gap between cutting-edge AI research and production-level software engineering? Our client, a leading innovator in the technology space, is seeking an experienced AI Architect to design and scale their proprietary Large Language Model (LLM) infrastructure, agent orchestration, and context layers.
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In this role, you will be pivotal in creating secure, scalable, multi-agent ecosystems while ensuring the organization maintains flexibility and avoids vendor lock-in. You will navigate "build vs. buy" decisions, establish reusable design patterns, and draft Architectural Decision Records (ADRs) that empower cross-functional data, ML, and application teams to execute with absolute clarity.
Advantages
Cutting-Edge Tech Stack: Work at the absolute forefront of Generative AI, multi-agent systems, and production-level LLM orchestration.
High Autonomy: Shape the foundational AI architecture and governance patterns for an enterprise-scale ecosystem.
Remote/Hybrid Flexibility: Enjoy a modern, flexible work environment tailored to high-performing technical leaders.
Impactful Growth: Lead complex "build vs. buy" architectural decisions with significant executive visibility.
Responsibilities
Agentic Ecosystem Design: Architect framework-agnostic multi-agent systems, workflows, and autonomous reasoning loops to build intelligent automation that interacts seamlessly with external resources.
Tool & Memory Integration: Abstract core agent services by integrating external tools, building semantic memory endpoints, and managing complex conversational states.
Context Layer Engineering: Ground systems in enterprise realities by architecting robust Retrieval-Augmented Generation (RAG) pipelines, integrating vector search, and optimizing context window limits.
Model Routing & Governance: Define dynamic, cost-aware, and latency-optimized model routing strategies across both open-source and proprietary foundation models.
AI Security & FinOps: Architect defense-in-depth frameworks, establish per-agent IAM/IAP identity controls, and enforce system-level token budgets.
Observability & Evaluation: Instrument systems with open telemetry to continuously monitor for latency, manage hallucinations, and drive automated prompt refinement.
Qualifications
Must-Have Qualifications
- Technical Support: Proven experience providing high-level technical support, guidance, and mentorship to cross-functional engineering, data, and ML teams.
Core Requirements & Skills
- GenAI/LLM Experience: Proven track record operationalizing LLM-driven application architecture patterns, prompt engineering, and agentic workflows.
- Programming: Strong coding foundation with a minimum of 4 years of dedicated, hands-on experience using Python.
- ML Ecosystems: In-depth knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow), vector databases, and modern LLM orchestration libraries.
- Cloud & Infrastructure: Hands-on experience with major cloud AI platforms (such as Amazon SageMaker, Azure AI, or Google Cloud Vertex AI) alongside deep API-based integration expertise.
Summary
This AI Architect position is a senior-level, highly technical role designed for a visionary engineer who thrives on turning theoretical GenAI capabilities into robust, secure, and highly efficient enterprise realities. If you have the required Python depth, a passion for multi-agent workflows, and a talent for cross-functional technical leadership, we want to hear from you.
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
show more
Are you an expert in bridging the gap between cutting-edge AI research and production-level software engineering? Our client, a leading innovator in the technology space, is seeking an experienced AI Architect to design and scale their proprietary Large Language Model (LLM) infrastructure, agent orchestration, and context layers.
In this role, you will be pivotal in creating secure, scalable, multi-agent ecosystems while ensuring the organization maintains flexibility and avoids vendor lock-in. You will navigate "build vs. buy" decisions, establish reusable design patterns, and draft Architectural Decision Records (ADRs) that empower cross-functional data, ML, and application teams to execute with absolute clarity.
Advantages
Cutting-Edge Tech Stack: Work at the absolute forefront of Generative AI, multi-agent systems, and production-level LLM orchestration.
High Autonomy: Shape the foundational AI architecture and governance patterns for an enterprise-scale ecosystem.
Remote/Hybrid Flexibility: Enjoy a modern, flexible work environment tailored to high-performing technical leaders.
Impactful Growth: Lead complex "build vs. buy" architectural decisions with significant executive visibility.
...
Responsibilities
Agentic Ecosystem Design: Architect framework-agnostic multi-agent systems, workflows, and autonomous reasoning loops to build intelligent automation that interacts seamlessly with external resources.
Tool & Memory Integration: Abstract core agent services by integrating external tools, building semantic memory endpoints, and managing complex conversational states.
Context Layer Engineering: Ground systems in enterprise realities by architecting robust Retrieval-Augmented Generation (RAG) pipelines, integrating vector search, and optimizing context window limits.
Model Routing & Governance: Define dynamic, cost-aware, and latency-optimized model routing strategies across both open-source and proprietary foundation models.
AI Security & FinOps: Architect defense-in-depth frameworks, establish per-agent IAM/IAP identity controls, and enforce system-level token budgets.
Observability & Evaluation: Instrument systems with open telemetry to continuously monitor for latency, manage hallucinations, and drive automated prompt refinement.
Qualifications
Must-Have Qualifications
- Technical Support: Proven experience providing high-level technical support, guidance, and mentorship to cross-functional engineering, data, and ML teams.
Core Requirements & Skills
- GenAI/LLM Experience: Proven track record operationalizing LLM-driven application architecture patterns, prompt engineering, and agentic workflows.
- Programming: Strong coding foundation with a minimum of 4 years of dedicated, hands-on experience using Python.
- ML Ecosystems: In-depth knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow), vector databases, and modern LLM orchestration libraries.
- Cloud & Infrastructure: Hands-on experience with major cloud AI platforms (such as Amazon SageMaker, Azure AI, or Google Cloud Vertex AI) alongside deep API-based integration expertise.
Summary
This AI Architect position is a senior-level, highly technical role designed for a visionary engineer who thrives on turning theoretical GenAI capabilities into robust, secure, and highly efficient enterprise realities. If you have the required Python depth, a passion for multi-agent workflows, and a talent for cross-functional technical leadership, we want to hear from you.
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
show more
