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BrightAI · 2 months ago

Senior AI Engineer – LLM, RAG

Palo Alto, CA

Full-time

Onsite

Senior Level

5+ years exp

Bright.AI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. The Senior AI Engineer – LLM, RAG will lead the development of Retrieval-Augmented Generation systems that leverage large language models to create intelligent assistants for troubleshooting in industrial settings.

Artificial Intelligence (AI)Cloud ComputingInternet of ThingsMobile

Responsibilities

Lead the architecture and development of RAG systems that combine 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 scenarios

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 settings

Stay up to date with the latest advances in LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap

Qualification

Large Language ModelsRetrieval-Augmented GenerationMachine LearningPrompt EngineeringDocument RetrievalPython ProgrammingProblem-SolvingCommunication SkillsCollaboration Skills

Required

M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field, with specialization in NLP or deep learning

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 was built

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)

Proficiency with ML development frameworks such as PyTorch, Hugging Face Transformers, or similar. 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 skills; ability to design solutions for complex, ambiguous problems

Strong written and verbal communication skills, with ability to collaborate cross-functionally with engineers, product managers, and domain experts

Preferred

Strong research or applied background in large language models (LLMs) and retrieval-augmented generation (RAG) systems. Agentic RAG experience is highly desirable

Experience applying LLMs in industrial or physical infrastructure settings (e.g., manufacturing, logistics, utilities, energy)

Knowledge of industrial control systems, maintenance workflows, or technician support processes

Exposure to multimodal models or integrating textual data with sensor and/or time-series data

Prior experience in a startup or a fast-paced environment building LLM-powered products from the ground up