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Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and evaluation loops while integrating enterprise APIs and ensuring robust CI/CD.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and evaluation loops with Python/TypeScript/Java.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; develop scalable agentic systems with Python/TypeScript/Java and modern frameworks.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating APIs and cloud services while owning end-to-end development and testing.
Builds AI-powered agentic applications (LLM tooling, RAG pipelines, vector search) from prototype to production, integrating with enterprise systems while ensuring scalability, safety, and observability.
Build AI-powered applications using LLMs, RAG pipelines, and vector search; implement agents, prompts, and evaluation loops with Python/TypeScript/Java and modern frameworks.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and evaluation loops while integrating enterprise APIs and data sources.
Build AI-powered applications using LLMs, RAG pipelines, and vector search; implement agents, prompts, and CI/CD while integrating enterprise APIs and data sources.
Build AI-powered applications using LLM tooling, RAG pipelines, and vector search; implement agents, prompts, and evaluation loops while integrating APIs and data sources.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases. Develop agents, prompts, and integrations with Python/TypeScript/Java, and deploy scalable prototypes.
Build AI-powered applications using LLMs, RAG pipelines, and vector search. Develop agents, prompts, and integrations with clean code and CI/CD, then prototype rapidly into production systems.
Build AI-powered applications using LLMs, RAG pipelines, and vector search; implement agents, prompts, and evaluation loops while integrating enterprise APIs and data sources.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and cloud services while delivering rapid prototypes.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and deploying scalable services with Java/Python/TypeScript.
Builds AI-powered agentic applications by implementing LLM tooling, RAG pipelines, and vector search, integrating with enterprise systems, and ensuring safety/testing. Core tech: Python, TypeScript/Node.js, Java, LangChain, vector DBs (pgvector, Pinecone).
Build AI-powered applications using Java full-stack, Python, and TypeScript, implementing agents, RAG pipelines, and vector search for rapid prototyping and production systems.
Advises on and experiments with agentic and generative AI systems to recommend scalable, responsible AI solutions for Desjardins Group’s AI initiatives.
Design and deploy enterprise AI solutions on Red Hat OpenShift AI, including GenAI, agentic AI, and MLOps workflows, while advising customers and leading project teams.
Advises on cutting-edge AI agent and generative AI technologies, runs experiments to validate frameworks like LangGraph, and turns findings into reusable best practices for Desjardins’s AI initiatives.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and ensuring robust testing and safety.
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