<p>The LLM Programmer will be responsible for building and optimizing applications that leverage large language models (LLMs) to solve business problems, improve user experiences, and automate complex workflows. You will work closely with engineering, product, and data teams to bring AI-driven features from concept to production.</p><p><strong>Key Responsibilities</strong></p><ul><li>Design and develop applications using large language models (e.g., GPT-style systems)</li><li>Build and maintain RAG (Retrieval-Augmented Generation) pipelines to integrate enterprise data with LLMs</li><li>Develop prompt engineering strategies and reusable AI workflows</li><li>Fine-tune or adapt models for domain-specific use cases when needed</li><li>Integrate LLM APIs into production systems and applications</li><li>Optimize performance, latency, cost, and accuracy of AI solutions</li><li>Evaluate model outputs for quality, reliability, and safety</li><li>Collaborate with cross-functional teams to identify and implement AI opportunities</li><li>Stay current with advancements in generative AI and LLM tooling</li></ul>

<p><strong>Required Qualifications</strong></p><ul><li>Experience in Python and backend development</li><li>Understanding of large language models and transformer-based architectures</li><li>Familiarity with LLM APIs (OpenAI, Anthropic, open-source models, etc.)</li><li>Experience with prompt engineering and AI system design</li><li>Knowledge of REST APIs and cloud environments (AWS, Azure, or GCP)</li><li>Strong problem-solving skills and ability to work in fast-paced environments</li></ul><p><strong>Preferred Qualifications</strong></p><ul><li>Experience building RAG systems using vector databases (Pinecone, FAISS, Weaviate, etc.)</li><li>Familiarity with frameworks like LangChain or LlamaIndex</li><li>Background in machine learning or natural language processing</li><li>Experience deploying AI applications in production at scale</li><li>Understanding of evaluation methods for LLM performance and hallucination mitigation</li></ul>

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