AI Expert developer

Description du poste

Position 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.

Qualifications requises

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).

Atouts supplémentaires

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.

Compétences

Skills:

• Data computing & Mlops
• English
• French
• Large Language Model (LLM)
• Model Context Protocol Servers
• Retrieval-Augmented Gen.(RAG)
• Anthropic Claude
• LangChain
• LangGraph
• OpenAI
• Python