About Millennium
Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium's mission is to deliver results for our investors.
Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.
Meet the Team
Core to the health and growth of our business, Millennium's Information Technology organization builds flexible, scalable platforms and advanced proprietary systems that support the firm's active, multi-manager model. Within this environment, the Business Development and Compensation Technology team owns platforms central to the firm's business development and incentive operating model, partnering across functions to deliver scalable, well-controlled systems aligned with evolving business and reporting needs.
What You'll Do
- Build, test, and deploy production-grade AI solutions using generative AI techniques, including LLMs, RAG, fine-tuning, prompt optimization, and agentic workflows
- Help redesign how business development activity is modeled, processed, controlled, and reported across the firm
- Shape AI-first systems architecture across multiple platforms supporting business development and incentive workflows
- Design and implement evaluation frameworks to measure solution quality, robustness, reliability, and business impact
- Partner closely with product managers, data engineers, and business stakeholders to translate business needs into scalable, production-ready solutions
- Contribute to real-time and batch data pipelines, including monitoring, logging, metrics, guardrails, and human-in-the-loop review processes
- Work across regions and departments to understand business workflows, contractual documents, and unstructured data, and apply those insights to effective AI solution design
- Perform data cleansing, data engineering, and pipeline development to make AI solutions reliable, scalable, and production-ready
What You Bring
- 5–6 years of data engineering experience, including 1–2 years of hands-on AI experience
- Experience building production-grade generative AI solutions at enterprise scale, including Model Context Protocols (MCPs), agent architectures, and Retrieval-Augmented Generation (RAG); exposure to GraphRAG is a plus
- Strong hands-on experience with Python, AWS, Bedrock, LLMs, RAG, and agentic AI
- Strong working experience in Linux environments and with AI coding tools such as Cursor, Copilot, and Claude
- Familiarity with agent orchestration frameworks such as LangGraph, Pydantic, or similar tools is highly desirable
- Experience with workflow orchestration tools such as Airflow or Temporal for running agentic flows and batch jobs
- Strong understanding of LLMs, RAG, prompt engineering, conversational AI platforms, and modern AI-powered user experiences
- Bachelor's degree in Computer Science or a related field
- If you want, I can also tighten this further into a more external-facing, candidate-marketing version while keeping the same facts.
