Software Engineer – Efficiency Engineering & AI Enablement

About the role

Join Millennium’s Efficiency Engineering & AI Enablement team to design and deliver internal applications, automation, and AI‑driven tools that boost productivity across Production Support and Quality Engineering. You will translate operational challenges into secure, maintainable solutions that leverage large language models and modern cloud technologies.

Key responsibilities

• Design, build, and ship internal applications, workflow automation, and productivity tools.
• Develop AI‑enabled solutions for knowledge assistance, incident analysis, test‑case generation, defect analysis, and engineering productivity.
• Rapidly prototype operational challenges and evolve successful prototypes into production‑grade services.
• Integrate large language models via APIs, open‑source libraries, prompt engineering, retrieval‑augmented generation, and agentic workflows.
• Collaborate with Production Support, Quality Engineering, and engineering stakeholders to gather requirements, validate solutions, and drive adoption.
• Build and maintain backend services, APIs, and frontend interfaces using modern frameworks and cloud platforms.
• Package, deploy, and support containerized applications in cloud environments.
• Define and track measurable outcomes such as time saved, reduced manual effort, faster testing cycles, and improved incident response.

Required profile

• Bachelor’s degree in Computer Science or a related field.
• 2–5 years of professional software engineering experience building applications, internal tools, or automation solutions.
• Proficiency in modern backend languages and frameworks (e.g., Python with FastAPI or Java with Spring Boot).
• Experience building frontend applications using React, Next.js, or Angular.
• Working knowledge of relational databases, preferably PostgreSQL.

Required skills

• Python
• FastAPI
• Java
• Spring Boot
• React
• Next.js
• Angular
• PostgreSQL
• Cloud platforms (AWS, Azure, or GCP)
• Containerization (Docker, Kubernetes)
• API design and implementation
• Large language model integration and prompt engineering