AI Solutions Architect

AI Solutions Architect at Deloitte

Deloitte is seeking an AI Solutions Architect - Generative AI to design, build, and guide the delivery of enterprise-grade GenAI solutions that solve real business problems at scale.

Our Purpose

At 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. As the largest 100% Canadian-owned and operated professional services firm, we are proud to work alongside our clients to make a positive impact for all Canadians.

What will your typical day look like?

This role combines hands-on solution architecture, platform thinking, and technical leadership. You will define patterns across LLMs, Retrieval-Augmented Generation (RAG), multi-agent systems, and orchestration frameworks while ensuring solutions are secure, scalable, cost-aware, and production-ready.

Key Responsibilities

• Generative AI Architecture: 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 model ecosystems. Design multi-agent patterns, tool integration frameworks, and orchestration approaches. Translate business needs into scalable, reusable architecture patterns.
• Platform & Cloud Enablement: Architect solutions primarily on Microsoft Azure, including Azure OpenAI, Azure AI Search / vector databases, Azure Functions, Container Apps, and 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.
• Engineering & Production Readiness: Apply strong software engineering fundamentals: API design and integration, CI/CD and DevOps practices, testing, monitoring, and 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.
• AI Governance & Responsible Use: 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.
• Leadership & Enablement: 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.

About The Team

The Enterprise Architecture team comprises enterprise, solution, data, and AI architects that define and scale solutions and strategies across the organization. We operate at the intersection of architecture, engineering, and business transformation — designing reusable patterns, production-ready platforms, and enterprise guardrails that enable responsible AI adoption at scale. Our focus is not isolated proofs of concept; we build foundational capabilities that integrate into core platforms and products, accelerate delivery teams, and shape the organization’s operating model. This role reports into Enterprise Architecture and partners closely with engineering, data, security, and business stakeholders across multiple portfolios.

Required Qualifications

• 5+ years of experience in software engineering, solution architecture, or related technical roles.
• Demonstrated experience designing and delivering cloud-based solutions in production environments.
• Hands-on experience building or architecting Generative AI solutions using LLMs.
• Strong expertise in Azure cloud architecture and services.
• Practical experience with RAG architectures and vector search, multi-model ecosystems (e.g., GPT, Anthropic, Gemini), and 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.

Nice to Have

• Experience with Google AgentSpace or other enterprise agent platforms.
• 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.

What Success Looks Like

Success in this role means 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, and the organization’s AI capabilities mature through structured architecture and responsible scaling.

Total Rewards

The salary range for this position is $85,000 - $156,000 CAD, and individuals may be eligible to participate in our bonus program. Deloitte offers a competitive base salary, variable pay opportunities, and a wide array of initiatives including $4,000 per year for mental health support, a $1,300 flexible benefit spending account, firm-wide closures ("Deloitte Days"), dedicated learning days, and flexible/hybrid work arrangements, designed to recognize employee contributions, encourage personal wellness, and support firm growth.

Key skills/competency

• Generative AI
• LLMs
• Azure Cloud
• Solution Architecture
• RAG (Retrieval-Augmented Generation)
• DevOps
• API Design
• AI Governance
• Scalable Systems
• Technical Leadership