Senior AI Engineer – LLM, RAG
Brightai · Palo Alto, CA
About this role
**Senior AI Engineer – LLM, RAG** **About BrightAI** BrightAI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. Our AI platform processes visual, spatial, and temporal data from billions of real-world events—captured across edge devices, mobile sensors, and cloud infrastructure—to enable intelligent decision-making at scale. We’re hiring a **Sr. AI Engineer – LLM, RAG** to lead the development of Retrieval-Augmented Generation (RAG) systems that combine large language models (LLMs) with real-world knowledge sources. This role is pivotal to building next-generation intelligent assistants that help technicians and operators troubleshoot complex issues in industrial settings. You’ll work at the intersection of **NLP, foundational models, and real-time information systems**, developing tools that turn manuals, technician notes, and sensor data into actionable, conversational guidance for the physical world. --- ### Responsibilities - Lead the architecture and development of RAG systems combining LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources. - Develop AI-powered assistants to support technicians in diagnosing and resolving anomalies or failures in factory, plant, or industrial settings. - Build pipelines to ingest, preprocess, and index large corpora of documents (manuals, logs, notes, procedures) for semantic search and grounding. - Customize and fine-tune foundational models to incorporate domain-specific language, tone, and logic for industrial troubleshooting. - Collaborate with product, data, and cloud teams to design scalable, privacy-compliant, and latency-sensitive LLM applications. - Design evaluation strategies to measure performance, accuracy, and user experience of RAG-enabled systems in production. - Stay up to date with advances in LLM architectures, retrieval methods, and prompt engineering; integrate emerging techniques into the product roadmap. --- ### Educational Background - M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field, with specialization in NLP or deep learning. - Strong research or applied background in LLMs and RAG systems (Agentic RAG experience is highly desirable). --- ### Required Skills & Expertise - 5+ years of experience in machine learning or AI with a strong focus on NLP, LLMs, or conversational AI. - Fluency with modern LLMs and open-source foundational models (e.g., LLAMA, Falcon, Mistral, GPT, Claude). - Experience building RAG pipelines with tools like **LangChain**, **LlamaIndex**, or custom vector database integrations, with at least one production-grade system. - Fluency with prompt engineering, instruction tuning, or fine-tuning open-source models. - Deep understanding of document retrieval (semantic search, embedding generation, similarity metrics) and vector stores (e.g., FAISS, Weaviate, Pinecone). - Strong foundation in core ML techniques, including experience with reinforcement learning (RL) or decision-making models. - Proficiency with ML development frameworks such as **PyTorch** and **Hugging Face Transformers**; strong **Python** programming is a must. - Experience integrating AI systems into real-world applications with user-facing interfaces and operational constraints. - Excellent problem-solving and critical thinking; ability to design solutions for complex, ambiguous problems. - Strong written and verbal communica
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