solutions architect v- full stack solution architect.

Our client, is seeking an experienced, highly strategic Solutions Architect V - Full Stack Solution Architect to join their Infrastructure and Engineering (I&E) group as a key member of the Solution Architecture Practice.

In this high-impact, independent contributor role, you will act as a principal technical authority and strategic advisor to the Infrastructure and Engineering organization. You will define target-state AI and platform architectures, help prioritize product roadmaps, and collaborate closely with technology squads to deliver production-ready, scalable solutions. The ideal candidate will design end-to-end Generative AI, LLM, and agentic AI solution architectures—including AI/LLM gateways, Retrieval-Augmented Generation (RAG) frameworks, vector search, model access patterns, AI observability, and security guardrails—ensuring seamless, governed integration across hybrid and multi-cloud environments.

Duration: 24-Month Contract (with high potential for extension or permanent conversion)

Work Arrangement: Hybrid (Currently 2 days per week on-site at the corporate office, subject to operational updates)

Advantages

Multi-Year Strategic Stability: Secure a 2-year enterprise consulting engagement with potential for contract extension or permanent conversion.

Cutting-Edge AI Scope: Direct the architectural vision, reference models, and deployment patterns for enterprise-grade Generative AI, agentic systems, and LLM gateways.

Principal Advisory Impact: Serve as a top-tier technical authority advising executive product owners, platform leads, and enterprise risk committees.

Hybrid Cloud Ecosystem: Architect multi-cloud and hybrid environments leveraging leading cloud AI platforms, Kubernetes-based workloads, and modern MLOps/AIOps tooling.

Responsibilities
Strategic AI & Solution Architecture
Target-State Blueprinting: Lead the design of end-to-end AI solution architectures, blueprint specifications, and high/low-level designs for GenAI platforms, AI/LLM gateways, agentic workflows, RAG, and vector search systems.

Roadmap & Portfolio Governance: Partner with Executive Product Owners to prioritize architecture backlogs, evaluate build vs. buy decisions, and align technology roadmaps with enterprise business goals.

Reference Architecture & Reusable Patterns: Establish reusable AI reference architectures, decision frameworks, and deployment patterns addressing model routing, semantic caching, fallback resiliency, token limits, and prompt controls.

Security, Risk & Governance
Responsible AI & Security Guardrails: Define security frameworks covering identity and access management (IAM), data protection, prompt injection/jailbreak mitigations, content safety, and audit logging.

Regulatory & Compliance Alignment: Collaborate with internal audit, cyber security, privacy, and risk governance groups to ensure AI workloads adhere to enterprise compliance standards and regulatory expectations.

Observability & Operational Excellence: Set service-level objectives (SLOs) and observability standards to deliver transparent tracing, logging, cost governance, and production supportability across multi-cloud environments.

Technical Leadership & Mentorship
Cross-Functional Collaboration: Work across platform engineering, data, security, and marketing teams to guide technology selection and ensure production readiness.

Practice Upskilling: Mentor and coach engineers and solution architects within the practice, building organizational capability around modern AI engineering and Kubernetes containerization.

Qualifications
Professional Architecture Experience: 15+ years of progressive IT experience designing and delivering enterprise platforms, complex system integrations, and infrastructure architectures.

Generative & Agentic AI Depth: Extensive hands-on architecture experience designing enterprise GenAI and agentic AI solutions (including AI agents, LLM gateways, RAG, vector search, prompt orchestration, and MCP/tool integration).

Cloud Platform Mastery: Deep understanding of AI platform architectures across cloud and hybrid environments, with specific experience in Azure OpenAI, Azure AI Foundry, and Google Vertex AI/Gemini.

Governance & Safety Controls: Intimate knowledge of AI operational controls, including token/cost management, prompt/response safety, semantic caching, auditability, and fallback resiliency.

Education: Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline (Master’s degree preferred).

Preferred Assets & Nice-to-Haves
Experience operating within a highly regulated corporate or financial services environment.

Modern software engineering experience with CI/CD pipelines, Pair Programming, or Test-Driven Development (TDD) frameworks.

Industry certifications in Cloud Architecture, AI Architecture, Responsible AI, MLOps, Kubernetes, or Enterprise Architecture Frameworks (e.g., TOGAF, Azure/GCP Solution Architect, Certified Kubernetes Administrator).

Summary
If you are a tech-savvy Full Stack Solution Architect who pairs 15+ years of enterprise IT leadership with deep architecture expertise in Generative AI, agentic frameworks, LLM gateways, and multi-cloud infrastructure, this 24-month contract opportunity is an extraordinary next step. Bring your architectural vision, AI governance precision, and collaborative leadership to our client's team today!

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 View email address on randstad.com to ensure their ability to fully participate in the interview process.

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