Applied Cloud and AI Engineer - Equities Cloud Platform Technology

Applied Cloud and AI Engineer - Equities Cloud Platform Technology 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 Technology is core to the health and growth of Millennium’s business. The firm’s active, multi-manager model demands flexible, scalable technology and advanced proprietary systems, including the next generation of analytical and trading capabilities. The Equities Platform and Cloud Engineering team operates at the intersection of applied AI, cloud infrastructure and DevOps, supporting production-grade platforms and systems in a fast-moving engineering environment.

Build and maintain secure, cloud-native infrastructure spanning compute, storage, networking, identity and access management, secrets management, logging and monitoring. Own CI/CD pipelines, infrastructure as code, containerization and deployment automation for AI and cloud platform services. Design, build and deploy production-ready LLM applications, multi-step AI agents and agentic workflows using orchestration, tool calling, memory and structured outputs. Integrate vector databases, graph databases, APIs and internal platforms to enable complex retrieval and automation use cases. Build Agent Harness infrastructure that manages LLM calls, tool usage, retries, policy enforcement and reusable agent execution patterns. Develop Agent Flywheel pipelines that capture traces, identify regressions, route failures into evaluation workflows and improve prompts, tools and models using production signals. Implement evaluation suites and deployment gates that measure task success, tool-selection accuracy, hallucination rates, latency, cost and overall agent quality. Partner across engineering and product teams to move solutions from prototype to production, prioritizing reliability, scalability, security and operational excellence. ​ What You Bring   Bachelor’s or master’s degree in Computer Science, Engineering or a related field, or equivalent practical experience. Hands-on experience developing LLM applications, AI agents, prompt engineering or retrieval-augmented generation systems. Experience with agentic AI frameworks such as Google ADK, PydanticAI, Claude Agent SDK or similar technologies, including tool-based architectures, MCP servers, hooks, plugins or skills. Strong Python software engineering skills and experience building production APIs and services. At least one year of experience with AWS, Azure or GCP and modern cloud architecture patterns. At least one year of experience with Docker, Kubernetes, Terraform and CI/CD workflows, with familiarity in deployment tools such as GitHub Actions or ArgoCD. Familiarity with vector and graph databases, data integration patterns and observability tools such as Grafana, Prometheus or Datadog. A proactive, creative and ownership-driven approach, with the ability to balance AI experimentation with disciplined engineering, security, access control and production reliability.

Millennium offers a total compensation package which includes a base salary, discretionary performance bonus, and comprehensive benefits. The estimated base salary range for this position is $100,000 to $175,000, which is specific to New York and may change in the future. When finalizing an offer, we take into consideration an individual’s experience level and the qualifications they bring to the role to