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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.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and ensuring robust testing and safety.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating APIs and cloud services while writing clean, testable code and CI/CD pipelines.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and APIs while owning full-stack development and CI/CD.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and CI/CD while integrating enterprise APIs and ensuring safety.
Job Description What is the opportunity? Join RBC as a hands-on technical lead building production-grade GenAI and Agentic AI applications for Cyber, Risk, Regulatory, Control & Security domains. This is an…
Build and deploy LLM-powered tools, RAG systems, and agentic workflows for autonomous aircraft systems, focusing on retrieval quality, tool integrations, and production-grade AI infrastructure on Kubernetes.
Design and build scalable data pipelines using Databricks, Snowflake, and Spark, leading architecture decisions and optimizing performance across AWS/GCP/Azure for client projects.
Build and maintain cloud-native geospatial platforms that ingest, process, and serve Earth Observation data via APIs and microservices using Python, Kubernetes, and open standards like STAC/OGC.
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