Poste d'Architecte - I'M IN ARCHITECTURE
$115k - $165k per yearAI and GenAI Architect
The Emerging Technologies team in Global Technology and Operations (GTO) Canada at CGI is a trusted Data, Cloud and AI advisor and go-to implementation partner for our global clients' Data and Advanced Analytics needs. We're an entrepreneurial team that is on a continuous mission to position CGI as the best-in-class AI partner and develop new and exciting opportunities in latest technologies.
The role requires strong, hands-on experience in developing Generative AI solutions, including agentic AI projects. It combines practical technical work with architectural responsibilities, rather than focusing solely on high‑level design. The position involves delivering rapid proofs of value for clients under tight timelines, followed by leading full-scale production implementations that ensure an optimal user experience and successful adoption.
As an AI and Generative AI Architect on our team, your responsibilities will include:
- Leading a client or internal CGI project as the Technical Architect and Lead - architecting solutions and also contributing in part hands-on to solution development
- Building Large Language Models-based and Agentic AI based solutions for CGI clients by researching the best in class techniques and being a self-starter with newer technologies
- Having strong architectural acumen designing solution architectures for AI and Agentic AI solutions
- Mitigating risks and optimizing costs associated with choosing a GenAI architecture solution and advise clients on best practices in Agentic AI
- Helping data engineer and prompt engineer the LLM solutions end-to-end to enhance end user experience
- Being "hands-on" to build, tune, deploy and monitor (MLOps and LLMOps) robust Machine Learning solutions built on RAG and latest GenAI techniques
- Helping fine-tune LLMs with latest cost optimized PEFT techniques like LoRA, QLoRA
- Strategically and intensely collaborating with innovation team and the client stakeholders and account teams to ideate and build key GenAI solutions
- Collaborating with other Data Scientists and Data Engineers in a client engagement setting and leading the delivery of work
- Implementing proof of concepts to show value and then package and scale to full ML solutions at scale on both on-prem and cloud environments
Architecture design and solution design experience with Agentic AI and Traditional AI solutions - including aspects like cost, scalability, security, performance, and maintainability
· Hands-on work experience with implementing Generative AI, LLMs, or GenAI solutions on at least 2-5 different projects or at least 1 project that was deployed in production
Hands on Implementation experience with Azure Foundry, Azure Promptflow, Langgraph, Amazon Bedrock, Google Vertex AI, Crew.ai et al latest agentic tech stacks
- Prompt Engineering experience on tools such as Azure Promptflow, Amazon Bedrock, Azure AI Studio would be ideal
- Experience building LLM-based solution on Azure, AWS or GCP
- Experience fine-tuning LLMs with latest techniques
- Experience with multiple models including open source models deployment (LLaMa, Mistral et al)
- Experience with multiple Vector Databases
- 5 or more years "hands-on" working experience delivering diverse Advanced Analytics and AI solutions
- Hands-on expertise in building and deploying code in Python, SQL and major programming languages with at least one major Cloud platform Azure, AWS, GCP
Experience with GenAI agents and agentic frameworks like Crew, Autogen and experience with recent Foundry Control Plane or similar control plane experiences
· The determination of this range includes various factors including but not limited to skill set level, geographic market, experience and training, and licenses and certifications. At CGI, we value the strength that diversity brings and are committed to fostering a workplace where everyone belongs. We collaborate with our clients to build more inclusive communities and empower all CGI partners to thrive.
$85k - $156k per year
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