AI Solution Architect (Solution Leadership)

Position Overview

The AI Solution Architect will be accountable for designing and overseeing the technical architecture of AI-enabled solutions throughout the program. Emphasis is placed on delivering practical and tangible value rather than focusing solely on theoretical innovations.

This role requires close collaboration with Enterprise Architects, Solution Architects, Engineering teams, DevSecOps specialists, and the AI Governance & Delivery Lead. The incumbent will establish AI reference architectures, select appropriate tools, and set implementation guidelines for the delivery teams. The position operates within an AI-first software engineering environment where AI integration spans the entire software development lifecycle.

Key Responsibilities

• Architect and govern AI-enabled solution frameworks across the program.
• Define and standardize AI reference architectures, reusable design patterns, and implementation guardrails for teams delivering AI features.
• Assess and advise on AI platforms, models, tooling, and integration methods suitable for enterprise deployments.
• Facilitate the adoption of AI software development lifecycle (AI SDLC) approaches and Business Model Assisted Development (BMAD) within engineering units.
• Work jointly with architecture and engineering divisions to embed AI capabilities within existing delivery ecosystems.
• Create guidelines for prompt management, AI-driven automation, and enhancements to developer productivity via AI.
• Ensure alignment of AI solutions with enterprise standards for architecture, security, privacy, and ethical AI usage.
• Participate in technical design reviews and provide mentorship regarding AI solution decisions.

Required Qualifications

• Over 10 years of experience in designing enterprise software solutions and application architectures.
• More than 5 years serving as a Solution Architect or Enterprise Architect in complex technical environments.
• Proven track record of designing and deploying enterprise AI-enabled solutions.
• Extensive experience with AI-augmented software development lifecycle practices.
• Hands-on implementation knowledge of BMAD or similar AI-native development frameworks.
• Expertise in designing cloud-native architectures, particularly on Microsoft Azure or comparable cloud platforms.
• Strong understanding of enterprise integration methods, including APIs, microservices, event-driven designs, and distributed systems.
• Familiarity with DevSecOps practices, continuous integration/continuous deployment (CI/CD), secure software engineering, and contemporary architectural principles.
• Excellent leadership, analytical thinking, communication, and stakeholder management capabilities.

Preferred Qualifications

• Experience building enterprise AI platforms or AI Centers of Excellence.
• Knowledge in advanced AI technologies such as Generative AI, Agentic AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI agents, or prompt engineering.
• Background integrating AI features into software engineering environments at enterprise scale.
• Certifications related to Azure AI, cloud computing, or enterprise architecture frameworks like TOGAF.
• Experience operating within highly regulated industries.

Company Culture and Values

Joining the team means becoming an owner from the start, contributing actively to the organization's strategy and success. The workplace emphasizes teamwork, respect, belonging, and personal growth. CGI partners benefit from a broad range of global resources to enhance skills and career paths. The company champions diversity and inclusion and commits to equitable hiring processes, including accommodations during recruitment.

CGI also responsibly applies AI in recruitment to assist but not replace human decision-making. Commitment to accessibility is a priority, with dedicated contact points for related requests.