AI Engineer (LLM/ Chatbot)

About The Role We are seeking an experienced AI Engineer to manage the design, deployment, and optimization of production-grade language model systems. This role involves building applications using both commercial LLM APIs and self-hosted open-source models, implementing RAG pipelines, and creating end-to-end LLM workflows. The ideal candidate combines practical experience integrating LLM APIs with technical expertise in deploying and optimizing local models. Key Responsibilities - Design and implement high-throughput, low-latency serving architectures for LLM applications - Build and maintain RAG pipelines and end-to-end LLM workflows - Integrate and optimize commercial LLM APIs (OpenAI, Anthropic, Google, etc.) into production systems - Develop prompt engineering techniques and prompt management systems - Deploy and serve local open-source language models for specific use cases - Optimize local model inference performance through efficient serving frameworks - Fine-tune models to improve performance on domain-specific tasks ( - Monitor and troubleshoot production LLM systems to ensure reliability - Research and experiment with emerging models and techniques to improve system capabilities - Document architectures, best practices, and technical decisions - Collaborate with engineering teams to integrate LLM capabilities into products - Communicate technical terms and recommendations to stakeholders - Build evaluation frameworks to measure model quality, latency, cost, and user satisfaction - Design intelligent routing and fallback strategies across multiple LLM providers - Scale LLM services to handle production workloads efficiently - Implement caching, batching, and request optimization strategies for both APIs and local models Experience Required Qualifications - Solid 2+ years focused on LLM applications or chatbot development (Candidates with more experience will be considered for a senior role.) - Proven track record of building production LLM applications - Experience integrating and optimizing commercial LLM APIs - Hands-on experience deploying local models in production environments Technical Skills - Strong Python programming with emphasis on async/await patterns and production-quality code - Deep understanding of transformer architectures and LLM fundamentals - Experience with LLM APIs (OpenAI, Anthropic Claude, Google Gemini, or similar) - Familiarity with local open-source models (Qwen, Llama, Mistral, or similar) - Experience with RAG implementation using LlamaIndex, LangChain or similar frameworks - Proficiency with FastAPI for building high-performance APIs - Experience with vector databases (Pinecone, Weaviate, Chroma, Milvus, or similar) - Working knowledge of MongoDB or other NoSQL databases - Experience with Docker containerization and deployment - Good to have hands-on fine-tuning experience (LoRA, QLoRA, full fine-tuning) - Familiarity with local model serving frameworks (vLLM, TGI, or similar) - Familiarity with LLM workflow tracing and observability frameworks (MLflow, Phoenix, Langfuse, or similar) - Familiarity with Hugging Face ecosystem and transformer libraries - Experience with cloud platforms (AWS, GCP, or Azure) - Proficiency with Git/GitHub and version control workflows Domain Knowledge - Understanding of prompt engineering and optimization techniques - Knowledge of LLM evaluation metrics and benchmarking methodologies - Experience with cost optimization for LLM applications - Familiarity with distributed computing and scaling strategies - Understanding of LLM inference optimization (quantization, batching, caching) Preferred Qualifications - Understanding of digital human technologies and multimodal applications - Knowledge of MLOps practices and CI/CD for ML systems - Experience with Kubernetes for container orchestration - Experience with streaming inference and real-time applications - Background in function calling and tool use with LLMs - Familiarity with RLHF (Reinforcement Learning from Human Feedback) - Experience with model distillation and knowledge compression - Understanding of distributed training and GPU optimization - Experience with multi-agent systems and LLM orchestration Soft Skills & Communication - Excellent English communication skills (written and verbal) - Excellent Chinese reading skill - Ability to explain complex technical concepts to both technical and non-technical audiences - Strong problem-solving and analytical thinking capabilities - Self-motivated with ability to work independently and drive projects to completion - Collaborative team player who thrives in fast-paced environments - Passion for staying current with rapidly evolving LLM technologies - Ability to balance research experimentation with production reliability requirements Excited to join us? Press APPLY or email your resume to jobs@pantheonlab.ai with: - The role you're applying for - Your availability - Expected salary We can’t wait to hear from you! NOTE: All personal data is collected for recruitment purposes only.

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