Responsibilities:
- Design, develop, and deploy autonomous and semi-autonomous AI agents to automate complex tasks across the software development lifecycle (SDLC).
- Design and implement MCP (Model Context Protocol) servers to integrate large language models (LLM) with internal systems, development tools, and enterprise data sources.
- Identify acceleration opportunities within the SDLC (code generation, code review, automated testing, documentation, deployment) and design tailored AI solutions.
- Develop robust prompt engineering pipelines and agent chains (multi-agent orchestration) to solve concrete business problems.
- Integrate generative AI solutions (LLM, RAG, agents) with existing DevOps tools (CI/CD, ticketing systems, version control, etc.).
- Collaborate with development, architecture, and operations teams to drive the adoption of AI practices within product teams.
- Ensure the quality, reliability, and observability of AI agents in production (monitoring, tracing, output evaluation).
- Actively monitor technological developments in LLMs, agent frameworks, and integration protocols (MCP, OpenAI function calling, tool use, etc.).
- Document architectures, technical decisions, and usage guides for internal teams.
Required Qualifications:
- Minimum 5 years of experience in software development, including at least 2 years focused on applied AI/ML.
- Hands-on experience developing AI agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or equivalents.
- Proficiency in setting up MCP servers and integrating LLMs via APIs (OpenAI, Anthropic, Azure OpenAI, etc.).
- Strong Python experience and solid knowledge of software development best practices (testing, code review, versioning).
- Experience with RAG (Retrieval-Augmented Generation) architectures and vector databases (Pinecone, Weaviate, pgvector, etc.).
- Good understanding of the SDLC and DevOps/MLOps practices (CI/CD, Docker, Kubernetes, Git).
- Ability to communicate complex technical concepts to non-technical stakeholders.
- Bilingual (French and English).
Additional Assets:
- Experience with AI-powered developer tools: GitHub Copilot, Cursor, Codeium, or similar solutions.
- Knowledge of agent integration protocols: MCP (Model Context Protocol), OpenAI Assistants API, tool use (Anthropic).
-Experience in LLM evaluation and benchmarking (LLM-as-a-judge, RAGAS, PromptFlow, etc.).
- AI/ML certification on a cloud platform (Azure AI Engineer, AWS ML Specialty, GCP Professional ML Engineer).
- Experience in a consulting or client project delivery context.
Your future duties and responsibilities
Required qualifications to be successful in this role
Together, as owners, let’s turn meaningful insights into action.
Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you’ll reach your full potential because…
You are invited to be an owner from day 1 as we work together to bring our Dream to life. That’s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company’s strategy and direction.
Your work creates value. You’ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise.
You’ll shape your career by joining a company built to grow and last. You’ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.
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. As an equal-opportunity employer, being able to perform your best during the recruitment process is important to us. If you require an accommodation, please inform your recruiter.
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