Posted Apr 21, 2026
Key Responsibilities:
Design, develop, and deploy LLM-based applications for AI-driven CRM solutions on Salesforce. - Implement Retrieval-Augmented Generation (RAG) architectures to optimize the contextual accuracy of LLMs within the Salesforce environment. - Leverage Vector Databases (e.g., Pinecone, FAISS, or Weaviate) to manage and retrieve high-dimensional data for AI applications. - Integrate external knowledge sources into AI models, enhancing their ability to deliver contextual and business-relevant insights. - Collaborate closely with cross-functional teams (including RevOps, data, and engineering) to ensure AI solutions align with business objectives and scale effectively. - Stay up-to-date with advancements in AI, including LLMs, RAG architectures, and innovations in database and cloud technology. Qualifications Required:
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. - Proven experience working with LLMs (e.g., GPT, BERT) and implementing them in production-level applications. - Expertise in RAG architecture for improving model relevance and performance in AI-driven systems. - Strong experience with Vector Databases to handle large-scale, high-dimensional data. - Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). - Familiarity with deploying AI/ML models on cloud platforms (e.g., AWS, Azure) with a focus on scalability. - Excellent problem-solving skills and ability to work collaboratively in a dynamic, fast-paced environment. Key Responsibilities:
Design, develop, and deploy LLM-based applications for AI-driven CRM solutions on Salesforce. - Implement Retrieval-Augmented Generation (RAG) architectures to optimize the contextual accuracy of LLMs within the Salesforce environment. - Leverage Vector Databases (e.g., Pinecone, FAISS, or Weaviate) to manage and retrieve high-dimensional data for AI applications. - Integrate external knowledge sources into AI models, enhancing their ability to deliver contextual and business-relevant insights. - Collaborate closely with cross-functional teams (including RevOps, data, and engineering) to ensure AI solutions align with business objectives and scale effectively. - Stay up-to-date with advancements in AI, including LLMs, RAG architectures, and innovations in database and cloud technology. Qualifications Required:
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. - Proven experience working with LLMs (e.g., GPT, BERT) and implementing them in production-level applications. - Expertise in RAG architecture for improving model rel
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