Platform Engineering Manager

Key Responsibilities

• Leadership of Platform / DevOps / SRE engineering teams, ensuring delivery excellence and strong engineering culture
• Ownership of internal platform products, working closely with product, application, and data engineering teams to deliver scalable, reliable, and secure platform capabilities.
• Support to Data Scientists, ML Engineers, Data Engineers, and Software Engineers by providing reliable, scalable, and easy-to-use platform services
• Definition and execution of the platform engineering strategy and roadmap, aligned with business and delivery objectives
• Development and operation of internal developer platforms enabling automation, self-service, and scalability
• Support to Data Scientists, Data Engineers, and Software Engineers by providing reliable, secure, and scalable platforms
• Cloud services: architecture and operations across AWS, Azure, and GCP, including compute, storage, networking, access management, cost monitoring, and cost optimization
• Infrastructure as Code: design, standardization, and governance using Terraform
• Containers: containerization and orchestration of applications using Docker and Kubernetes, including Kubernetes platform ownership
• CI/CD: definition and standardization of continuous integration and deployment pipelines
• Observability & reliability: monitoring, logging, alerting, and application of SRE principles to ensure availability, performance, and resilience
• Contribution to technological, architectural, and governance decisions to address the challenges of scaling AI and data platforms
• Collaboration with product, application, data, and security teams to gather requirements and deliver platform capabilities
• Planning and management of platform initiatives, including timelines, resourcing, and budget oversight
• Mentoring engineers and fostering knowledge sharing and continuous improvement.
• Experience: 8+ years of experience in the data/software space, with at least 3+ years in a formal people management or technical leadership role leading Data Science or ML teams.
• Strong hands-on experience with cloud platforms (AWS, Azure, and/or GCP)