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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.
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.
Leads AI/ML and generative AI projects, designing RAG pipelines, LLM-based systems, and production-ready models while owning end-to-end delivery, strategy, and cross-functional team leadership.
Job Description We are seeking experienced AI Engineers / Agentic AI Developers to design, develop, and deploy enterprise-grade AI solutions with a focus on Agentic AI , Large Language Models (LLMs) , and…
Own AI-focused data platform features from PRFAQ to launch, partnering with engineering and GTM to ship vector search, RAG, and agent frameworks for enterprise customers.
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