Data Scientist - R01572335

**Senior AI/ML Engineer** ### Job requirements **Experience Range:** 2 to 4 years of experience, including at least 2 years specifically focused on developing LLM-based applications, RAG systems, or AI agent workflows **Key Responsibilities:** - Design and build end-to-end AI agent workflows, from initial prompt design through production deployment, ensuring scalable and reliable solutions - Develop and optimize Retrieval-Augmented Generation (RAG) pipelines by implementing chunking strategies, embedding models, retrieval ranking, and context window management for precise information retrieval - Build and iterate on prompt engineering layers, systematically testing and refining prompts and chain-of-thought strategies to deliver consistent outputs across diverse inputs - Implement tool orchestration within agent workflows, integrating agents with databases, rule engines, validation systems, and formatting tools for seamless operation - Establish automated quality checks and validation layers to proactively identify and resolve issues before outputs reach human reviewers - Collaborate with Data Scientists to instrument solutions for measurement, developing evaluation frameworks and tracking solution performance against defined targets - Deploy, monitor, and maintain AI/ML solutions in production environments, ensuring reliability, scalability, and robust error handling - Design and implement feedback loops to capture expert review data and translate it into measurable improvements in agent performance **Required Skills:** - Advanced proficiency in Python - Hands-on experience with LLM frameworks such as LangChain or LlamaIndex - Expertise in prompt engineering for systematic testing and iteration - Deep understanding of RAG architectures including embedding models, vector stores, retrieval strategies, and re-ranking - Experience building multi-step agent workflows with tool use and branching logic - Experience deploying and maintaining AI/ML solutions in production environments - Experience with data pipeline development for feeding AI systems **Preferred Skills:** - Experience with multi-agent orchestration frameworks - Background in content generation, translation, or document processing solutions - Familiarity with feedback loops, RLHF, or reward model training - Knowledge of multi-modal AI systems including voice-to-text, document understanding, and image analysis - Experience with evaluation frameworks for generative AI and automated scoring - Experience with LLM cost optimization strategies such as model routing, caching, and prompt compression **Desired Qualifications:** - Bachelor's degree in Computer Science, Data Science, Information Technology, Statistics, or a closely related discipline - Certification in Machine Learning or Artificial Intelligence (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty) - Certification in LLM engineering or generative AI (e.g., Generative AI with LLMs)