AI Infrastructure Engineer
About the Role
Key Responsibilities
- Architect, build, and implement infrastructure to support large‑scale training and inference of generative AI models
- Design and optimize infrastructure for performance, scalability, cost efficiency, and responsible resource consumption
- Evaluate AI infrastructure options (cloud, platform, and tooling) and provide data‑driven recommendations
- Advise on technology and vendor selection to align with business and strategic objectives
- Develop operational controls, monitoring, and observability solutions for AI platforms
- Implement control towers to monitor, manage, and improve generative AI platform operations
- Collaborate with engineering, architecture, and delivery teams to support end‑to‑end AI solutions
Required Qualifications
- Advanced proficiency in Python, with strong hands‑on experience using the Pandas library
- Solid understanding of database architecture and data management concepts
- Minimum of 1 year of experience in relevant technology, data, or platform engineering roles
- Bachelor’s Degree in Computer Science, Engineering, Data Science, or a related field
- Ability to work independently while contributing effectively in team‑based problem solving
- Strong analytical, communication, and documentation skills
Preferred Qualifications
- Knowledge of advanced data architecture principles
- Experience in platform engineering or infrastructure automation
- Exposure to Tableau or other data visualization tools
- Familiarity with technology architecture blueprints and roadmap definition
Singapore
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