Publié il y a 25 jours
AI Expert developer
@ CGI
Montréal, Québec
SIGNAUX
En bref
CGI is hiring an AI Expert developer for a full-time role building autonomous AI agents and MCP servers that automate software development lifecycle tasks. The work covers LLM integration, RAG architectures, agent orchestration and DevOps tooling. Candidates need at least 5 years of software development experience, 2 of them in applied AI/ML.
Responsabilités :
- Concevoir et déployer des agents IA autonomes pour automatiser le cycle de développement logiciel
- Concevoir des serveurs MCP reliant les LLM aux systèmes internes et aux sources de données
- Intégrer les solutions d'IA génératives aux outils DevOps (CI/CD, gestion de tickets, contrôle de version)
- Assurer la qualité, la fiabilité et l'observabilité des agents IA en production
- Documenter les architectures et guides d'utilisation pour les équipes internes
Résumé des exigences :
- Minimum 5 ans d'expérience en développement logiciel, dont 2 ans en IA/ML appliquée
- Expérience pratique avec LangChain, LangGraph, AutoGen, CrewAI ou équivalents
- Maîtrise de la mise en place de serveurs MCP et de l'intégration de LLM via API
- Solide expérience en Python et bonnes pratiques de développement
- Expérience des architectures RAG et des bases de données vectorielles
- Bilingue français et anglais
Outils et compétences
Source et dates
Type de source non vérifié · njoyn
- Date publiée par l’employeur
- 2026-10-13
- Première détection par notre source
- 2026-10-17
- Mise à jour du dossier source
- 2026-10-17
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Senior |
| Domaine | Développement logiciel |
| Expérience | 5 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau, Domicile |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English, French |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
| Champ | Valeur |
|---|---|
| Taille | 10001+ |
| Siège social | E-Commerce Place |
| Offres sur Jobsy | 514 |
Description
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.
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.
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