Platform Engineer

We're looking for a Platform Engineer to build the backbone of applied artificial intelligence for our customers. You will design, build, and deploy robust, secure, and scalable cloud infrastructure that powers cutting-edge data and machine learning workflows. Working in a cross-functional team, you'll solve complex challenges and empower our data scientists and ML engineers to deploy their work effectively, shaping the future of AI solutions.

Responsibilities:

• Building robust, secure, and scalable cloud infrastructure for AI and ML workflows.
• Partnering with technical and non-technical stakeholders, from initial idea generation through to implementation and shipping.
• Enabling Machine Learning Engineers and Data Scientists by contributing to internal best practices, standards, and reusable code repos.
• Proactively identifying and recommending new ways customers can leverage cloud infrastructure to solve their key challenges.
• Creating and maintaining reusable, company-wide libraries and infrastructure-as-code.
• Researching and integrating the best open-source technologies to enhance Faculty's infrastructure capabilities.

Requirements:

• You are pragmatic and outcome-focused, balancing the big picture with the details to execute complex projects in the real world.
• You think scientifically, always testing assumptions, seeking evidence, and looking for opportunities to improve how things are done.
• You have a drive to learn, constantly exploring new technologies and novel applications for existing tools.
• You possess deep experience with both Azure and AWS as well as Infrastructure as Code, especially Terraform.
• You are experienced in building and deploying containerized solutions using Docker and Kubernetes, supported by strong CI/CD and GitOps practices.
• You possess proficient knowledge of Networking and Cloud Security.
• You excel at working directly with clients and stakeholders, confidently handling requirements gathering, technical planning, and scoping.