Based in New York, United States, Millennium is seeking an AI Engineer to design, build, and deploy production-grade AI solutions using generative AI techniques, including large language models, retrieval-augmented generation, fine-tuning, prompt optimization, and agentic workflows. You will redesign how business development activities are modeled, processed, controlled, and reported across the firm, and shape AI-first systems architecture across platforms that support business development and incentive workflows. You will design evaluation frameworks to measure solution quality, robustness, reliability, and business impact, and collaborate with product managers, data engineers, and business stakeholders to translate requirements into scalable, production-ready solutions. You will contribute to real-time and batch data pipelines, implementing monitoring, logging, metrics, guardrails, and human-in-the-loop review processes. You will work across regions and departments to understand business workflows, contractual documents, and unstructured data to design effective AI solutions, and perform data cleansing, data engineering, and pipeline development to ensure reliability and scalability. The ideal candidate has 5+ years of data engineering experience with 1–2 years of hands-on AI experience, experience building production-grade GenAI solutions at enterprise scale (including MCPs, agent architectures, and RAG, with GraphRAG as a plus), strong hands-on experience with Python, AWS, Bedrock, LLMs, RAG, and agentic AI, familiarity with agent orchestration frameworks such as LangGr

Based in New York, United States, Millennium is seeking an AI Engineer to design, build, and deploy production-grade AI solutions using generative AI techniques, including large language models, retrieval-augmented generation, fine-tuning, prompt optimization, and agentic workflows. You will redesign how business development activities are modeled, processed, controlled, and reported across the firm, and shape AI-first systems architecture across platforms that support business development and incentive workflows. You will design evaluation frameworks to measure solution quality, robustness, reliability, and business impact, and collaborate with product managers, data engineers, and business stakeholders to translate requirements into scalable, production-ready solutions. You will contribute to real-time and batch data pipelines, implementing monitoring, logging, metrics, guardrails, and human-in-the-loop review processes. You will work across regions and departments to understand business workflows, contractual documents, and unstructured data to design effective AI solutions, and perform data cleansing, data engineering, and pipeline development to ensure reliability and scalability. The ideal candidate has 5+ years of data engineering experience with 1–2 years of hands-on AI experience, experience building production-grade GenAI solutions at enterprise scale (including MCPs, agent architectures, and RAG, with GraphRAG as a plus), strong hands-on experience with Python, AWS, Bedrock, LLMs, RAG, and agentic AI, familiarity with agent orchestration frameworks such as LangGr