Data Scientist
best practices in development and deployment Desired Experience and Skills Experience with LLM-based solutions such as RAG...
best practices in development and deployment Desired Experience and Skills Experience with LLM-based solutions such as RAG...
: structured outputs, retrieval-augmented generation (RAG), or AI agent workflows....
, Agentic AI frameworks, and RAG architectures Automate provisioning, monitoring, troubleshooting, compliance validation... to Have Experience with GenAI and Agentic AI frameworks (e.g., LangChain, CrewAI, AutoGen, MCP) Exposure to LLMs, RAG architectures...
, observable, and business-oriented AI solutions leveraging LLMs, RAG pipelines, AI agents, and modern cloud-native architectures... and optimize Retrieval-Augmented Generation (RAG) pipelines and AI agents for enterprise use cases. Integrate and orchestrate LLM...
, observable, and business-oriented AI solutions leveraging LLMs, RAG pipelines, AI agents, and modern cloud-native architectures... and optimize Retrieval-Augmented Generation (RAG) pipelines and AI agents for enterprise use cases. Integrate and orchestrate LLM...
solutions Build and implement Agentforce AI agents, prompts, grounding (RAG), and custom agent actions Design and deliver...
, observable, and business-oriented AI solutions leveraging LLMs, RAG pipelines, AI agents, and modern cloud-native architectures... and optimize Retrieval-Augmented Generation (RAG) pipelines and AI agents for enterprise use cases. Integrate and orchestrate LLM...
-on experience with at least one vector database (Azure AI Search, Pinecone, Qdrant, or PGVector) Understanding of RAG (Retrieval...
NLU modeling, and omnichannel integrations. Integrate GenAI capabilities into production deployments: RAG pipelines... experience integrating GenAI/LLM capabilities into production systems: RAG, embeddings, prompt engineering, LLM APIs (OpenAI...
based solutions for a production environment. Experience with Generative AI and LLMs — prompt engineering, RAG...