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Senior / Principal Forward Deployed Engineering & AI Solutions Architect Category: Infrastructure/Cloud
Main location: Canada, Ontario, Toronto
Position ID:J1026-1264
Employment Type: Full Time
Position Description: CGI is seeking an accomplished, independent and commercially astute Senior / Principal Forward Deployed Engineering & AI Solutions Architect to help establish, evolve and deliver our Forward Deployed Engineering (FDE) service offering. This is a senior, hands-on technical leadership and business consulting role-not a traditional business analyst, advisory-only architect or staff-augmentation assignment.
The successful candidate combines deep software engineering and enterprise architecture expertise with exceptional business consulting capabilities and demonstrated experience designing, building, integrating and deploying AI-powered solutions. They can engage executive stakeholders, diagnose ambiguous business problems, shape investable opportunities, select appropriate technologies and lead implementation through production readiness, adoption and measurable business outcomes.
A central mandate is to develop, operationalize and continuously refine CGI's modular FDE delivery framework so it can be adapted to enterprise and mid-market clients, diverse technology stacks, different levels of organizational maturity, and varying security, regulatory and operational requirements. AI must be leveraged both to create valuable client solutions and, wherever appropriate, to accelerate the engineering lifecycle-without compromising security, quality, governance or human accountability.
Your future duties and responsibilities: Key Responsibilities
1. Business Consulting, Discovery & Value Realization
• Independently lead executive and operational stakeholder engagement to understand business priorities, process friction, operating constraints and opportunities for improvement.
• Facilitate discovery and solution-shaping workshops; translate ambiguous objectives into clearly scoped use cases, business requirements, acceptance criteria and prioritized engineering backlogs.
• Define baseline metrics, target KPIs, adoption measures, benefits hypotheses and value-realization plans; communicate trade-offs and progress in business terms.
• Assess feasibility, dependencies, investment, risk and delivery options; contribute to business cases, estimates, proposals, statements of work and client decision-making.
• Operate as a trusted advisor while remaining accountable for translating recommendations into delivered capabilities.
2. Hands-On Engineering & Enterprise Architecture
• Own technical solution direction from discovery and architecture through prototyping, implementation, integration, validation and production transition.
• Design secure, scalable, maintainable systems across modern applications, APIs, data services, cloud platforms and enterprise integrations; adapt architecture to client standards and constraints.
• Contribute hands-on to prototypes, critical code, technical spikes, integration patterns, code reviews and resolution of complex engineering issues.
• Lead multidisciplinary delivery teams, balancing engineering quality, velocity, cost, operational reliability and business value.
• Apply CI/CD, automated testing, DevSecOps, observability, documentation and release controls; coordinate production deployment under client-approved authorization processes.
3. AI Solution Development & AI-Accelerated Engineering
• Identify and qualify opportunities for generative AI, machine learning, intelligent automation and agentic workflows based on demonstrable business value and feasibility.
• Architect, develop and deploy AI-enabled applications, including LLM integrations, retrieval-augmented generation, tool-using agents, orchestrated workflows and human-in-the-loop decision processes where appropriate.
• Use approved AI coding assistants and agentic development workflows to accelerate analysis, design, code generation, refactoring, testing, integration, documentation and modernization.
• Evaluate models, platforms and frameworks against accuracy, latency, security, data protection, cost, maintainability and operational suitability; select conventional engineering where AI adds insufficient value.
• Implement AI evaluation, monitoring, guardrails, traceability, human oversight and appropriate governance for production-grade systems.
• Develop reusable prompts, agent patterns, evaluation harnesses, reference implementations and engineering accelerators; quantify delivery improvements where measurable.
4. FDE Framework Development & Adaptability
• Co-create and own the evolution of CGI's FDE delivery framework, including discovery, readiness, engineering execution, acceptance, production transition and continuous improvement.
• Build modular playbooks, reference architectures, delivery standards, templates, automation and reusable accelerators that can be configured for distinct client scenarios rather than imposed as a rigid methodology.
• Support both client-managed engineering environments and CGI-enabled toolchains, integrating with approved repositories, AI tools, CI/CD pipelines, governance and security controls.
• Define practical engagement entry criteria, optional readiness / Sprint 0 activities, iterative delivery cadences, technical quality gates, outcome measurement and handover practices.
• Capture lessons learned across engagements; improve mobilization speed, repeatability, solution quality and commercial scalability of the service.
5. Independent Client Delivery & Practice Leadership
• Lead engagements with minimal supervision, establish priorities, resolve ambiguity, manage dependencies and risks, and make accountable technical and delivery decisions.
• Collaborate directly with client Product Owners, business SMEs, security, architecture and operations teams; communicate clearly from executive steering discussions to engineering reviews.
• Mentor consultants and engineers; strengthen CGI's FDE capability through coaching, technical standards, demonstrations and knowledge sharing.
• Support go-to-market activities, opportunity qualification, solution demonstrations and the evolution of the service offering.
Required qualifications to be successful in this role:• Substantial senior-level experience in hands-on software engineering, solution architecture and client-facing technology consulting, including independent ownership of complex production deliveries.
• Proven ability to engage senior business stakeholders, lead discovery, shape solutions and connect engineering priorities to measurable business outcomes.
• Demonstrated hands-on development and deployment of AI-enabled solutions in real-world environments, with practical knowledge of LLM applications, agentic workflows, RAG, evaluation and integration.
• Advanced proficiency in at least one modern programming ecosystem (such as Python, TypeScript/JavaScript, Java or C#/.NET) and strong competency in APIs, cloud architecture, data integration and software engineering.
• Practical experience using AI-assisted engineering tools and workflows to accelerate software delivery, with judgment regarding quality, security and verification.
• Experience designing or improving repeatable delivery frameworks, engineering standards, reference architectures or reusable technical accelerators.
• Strong knowledge of CI/CD, testing, DevSecOps, security, observability, reliability and production-readiness practices.
• Ability to adapt delivery to client-owned or provider-enabled toolchains, organizational maturity and regulatory constraints.
• Exceptional written and verbal communication, stakeholder facilitation, commercial awareness and autonomous problem-solving skills.
Preferred Qualifications
• Experience in forward-deployed engineering, principal engineering, client-embedded solution architecture or technical consulting leadership.
• Experience establishing or scaling a consulting service, engineering practice or repeatable client delivery capability.
• Production delivery of enterprise agentic systems, multi-agent orchestration, AI-enabled workflows or intelligent automation.
• Experience with tools and ecosystems such as GitHub Copilot, Claude Code, Cursor, OpenAI-compatible APIs, LangGraph or comparable technologies; specific vendor expertise is not mandatory.
• Experience across AWS, Azure and/or Google Cloud and in regulated or security-sensitive environments.
• Experience supporting commercial solution shaping, estimates, proposals and statements of work; relevant architecture, cloud or AI credentials.
Measures of Success
• Client outcomes: delivered and adopted capabilities with clearly evidenced business value.
• Independent ownership: successful leadership from ambiguous opportunity through accepted, production-ready solution.
• Framework maturity: adaptable, documented delivery pathways and repeatable practices usable across different client scenarios.
• AI effectiveness: valuable AI solutions and demonstrable engineering acceleration with appropriate quality and governance controls.
• Practice growth: reusable assets, improved mobilization and contributions to client opportunities and team capability.
The Opportunity
This role offers the opportunity to help define a strategic capability within CGI Emerging Technologies: an embedded, AI-enabled engineering service that turns funded business priorities into secure, production-ready solutions. The ideal individual is equally credible in an executive discussion, an architecture review and a hands-on engineering session-and can build the repeatable framework that enables other teams to deliver at the same standard.
CGI is providing a reasonable estimate of the pay range for this role. The determination of this range includes factors such as skill set level, geographic market, experience and training, and licenses and certifications. Compensation decisions depend on the facts and circumstances of each case. A reasonable estimate of the current range is $110,000-$160,000. This role is an existing vacancy.
#LI-AB19
Use of the term 'engineering' in this job posting refers to the technical sense related to Information Technology (IT) and does not imply that the individual practices engineering or possesses the requisite license as prescribed by the applicable provincial or territorial engineering regulator. We are seeking individuals with expertise in IT engineering-related functions, but licensure from an engineering regulator is not a prerequisite for this position. Engineering is a regulated profession in Canada which is restricted in terms of use of titles and designation.
Use of the term 'architect' in this job posting refers to the technical sense related to Information Technology (IT) and does not imply that the individual practices architecture or possesses the requisite license as prescribed by the applicable provincial or territorial architect regulator. We are seeking individuals with expertise in IT architect-related functions, but licensure from an architect regulator is not a prerequisite for this position. Architecture is a regulated profession in Canada which is restricted in terms of use of titles and designation.
Skills: - Finance&Ops Apps Solution Arch
