AI Solutions Architect
Deloitte View all jobs
- Toronto, ON
- $85,000-156,000 per year
- Permanent
- Full-time
Work Model: Hybrid
Reference code: 132266
Primary Location: Toronto, ON
All Available Locations: Toronto, ON; Burlington, ON; Kitchener, ONOur PurposeAt Deloitte, our Purpose is to make an impact that matters. We exist to inspire and help our people, organizations, communities, and countries to thrive by building a better future. Our work underpins a prosperous society where people can find meaning and opportunity. It builds consumer and business confidence, empowers organizations to find imaginative ways of deploying capital, enables fair, trusted, and functioning social and economic institutions, and allows our friends, families, and communities to enjoy the quality of life that comes with a sustainable future. And as the largest 100% Canadian-owned and operated professional services firm in our country, we are proud to work alongside our clients to make a positive impact for all Canadians.By living our Purpose, we will make an impact that matters.
- Have many careers in one Firm.
- Enjoy flexible, proactive, and practical benefits that foster a culture of well-being and connectedness.
- Learn from deep subject matter experts through mentoring and on the job coaching
- Design and deliver end-to-end GenAI solutions from concept through production.
- Define architectures leveraging LLMs, RAG, agents, and orchestration frameworks.
- Architect multi-model strategies across GPT, Anthropic, Gemini, and related
- Design multi-agent patterns, tool integration frameworks, and orchestration approaches.
- Translate business needs into scalable, reusable architecture patterns.
- Architect solutions primarily on Microsoft Azure, including:
o Azure AI Search / vector databases
o Azure Functions, Container Apps, Kubernetes
- Design and implement solutions using Microsoft Copilot Studio and extensibility patterns.
- Leverage Google AgentSpace and related agent platforms where appropriate.
- Define integration patterns with enterprise systems and APIs.
- Ensure solutions follow cloud-native, resilient, observable, and cost-aware design principles.
- Apply strong software engineering fundamentals:
o CI/CD and DevOps practices
o Testing, monitoring, evaluation frameworks
- Establish patterns for prompt management, model evaluation, and versioning.
- Implement cost optimization strategies (token management, routing, caching).
- Partner with engineering teams to ensure production-grade implementations.
- Embed security, privacy, compliance, and responsible AI guardrails into architecture.
- Define patterns for human-in-the-loop workflows and risk mitigation.
- Collaborate with security, legal, and risk stakeholders to align with enterprise standards.
- Act as a trusted technical advisor to delivery teams and stakeholders.
- Present architecture options and trade-offs clearly to technical and executive audiences.
- Mentor engineers and architects in GenAI patterns and best practices.
- Contribute to reusable accelerators, reference architectures, and platform standards.
- 5+ years of experience in software engineering, solution architecture, or related
- Demonstrated experience designing and delivering cloud-based solutions in
- Hands-on experience building or architecting Generative AI solutions using LLMs.
- Strong expertise in Azure cloud architecture and services.
- Practical experience with:
o Multi-model ecosystems (e.g., GPT, Anthropic, Gemini)
o Agent-based architectures and orchestration frameworks
- Experience designing secure, scalable, and cost-aware cloud solutions.
- Experience with Microsoft Copilot Studio and Copilot extensibility patterns.
- Experience with token cost modeling and AI performance optimization.
- Knowledge of model evaluation frameworks, benchmarking, and drift monitoring.
- Strong grounding in API design, DevOps practices, and modern engineering patterns.
- Ability to translate business requirements into clear technical designs.
- Excellent communication and stakeholder management skills.
- Experience with Google AgentSpace or other enterprise
- Azure AI Fundamentals and Solution Architect Certifications
- GCP Certifications
- TOGAF
- Experience implementing multi-agent systems in production environments.
- Exposure to enterprise AI governance, compliance, and risk management frameworks.
- Experience contributing to enterprise platform strategy or AI operating models.
- Background in data engineering, embeddings pipelines, or semantic search optimization.
- GenAI solutions move efficiently from PoC to production with clear architectural standards.
- Reusable patterns and accelerators reduce duplication and accelerate delivery teams.
- AI solutions are secure, cost-managed, and aligned with enterprise governance.
- Stakeholders understand both the value and risks of GenAI initiatives.
- The organization’s AI capabilities mature through structured architecture