Software Engineer - Efficiency Engineering and AI Enablement

Millennium•Miami, FL

10d•$175,000 - $250,000

About The Position

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. Technology is core to the health and growth of Millennium’s active, multi-manager business model, which demands flexible, scalable technology and advanced proprietary systems. The Efficiency Engineering & AI Enablement team improves the speed, quality and effectiveness of the firm’s Production Support and Quality Engineering organizations. The team focuses on engineering productivity, workflow automation, software quality and the practical application of AI and large language model technologies.

Requirements

Bachelor’s degree in Computer Science or a related field.
Two to five years of professional software engineering experience building applications, internal tools, automation or engineering productivity solutions.
Proficiency in modern backend languages and frameworks, such as Python with FastAPI or Java with Spring Boot, along with experience building frontend applications using React, Next.js or Angular.
Working knowledge of relational databases such as PostgreSQL.
Hands-on experience with, or a strong demonstrated interest in, applying AI and LLM technologies to conversational tools, intelligent automation, summarization or AI-assisted workflows.
Familiarity with AWS or another cloud platform, Docker and containerized application development and deployment.
Ability to move quickly from idea to prototype to production while applying sound engineering judgment and maintaining quality, security and scalability.
Strong problem-solving, stakeholder partnership and communication skills, supported by a collaborative and feedback-driven working style.

Responsibilities

Design, build and deliver internal applications, automation and workflow tools that improve productivity, operational consistency, visibility and quality across Production Support and Quality Engineering.
Develop AI-enabled solutions for use cases such as knowledge assistance, incident analysis and triage, issue summarization, test-case generation, defect analysis and engineering productivity.
Rapidly translate operational challenges into working prototypes, then evolve successful solutions into secure, maintainable and scalable production applications.
Integrate large language models and AI capabilities into internal workflows using APIs, open-source libraries, prompt engineering, retrieval-augmented generation and agentic workflows.
Partner with Production Support, Quality Engineering and engineering stakeholders to identify requirements, validate solutions, incorporate feedback and drive adoption.
Build and maintain backend services, APIs and frontend interfaces using modern application development and cloud technologies.
Build, package, deploy and support containerized applications in cloud environments.
Define and track measurable outcomes, including time saved, reduced manual effort, faster testing cycles and improved incident response, while contributing through code reviews and knowledge sharing.