Senior AI Platform Engineer

Key Responsibilities

• Design and develop platform services for containerized model training, distributed computing, artifact management, and deployment automation.
• Build and maintain infrastructure that ensures scalability, reproducibility, and security of AI workflows across various environments.
• Implement CI/CD pipelines, observability frameworks, and developer tools to support multiple AI teams efficiently.
• Collaborate with cross-functional teamsincluding data scientists, ML engineers, architects, and developers—to deliver essential platform features.
• Champion automation, enforce performance and security best practices, and drive operational reliability across platform services.
• Provide technical mentorship and contribute to long-term architecture and platform strategy.
• Stay updated with the latest advancements in cloud infrastructure, AI/ML tooling, and platform engineering trends.

Skills & Qualifications

• 7+ years of experience in software or platform engineering, including at least 3 years working on infrastructure for data or AI systems.
• Demonstrated experience building infrastructure on GCP or AWS (GCP preferred).
• Proficiency in Python, Go, or JavaScript, with a focus on developing scalable and secure backend services.
• Strong knowledge of container orchestration (e.g., Kubernetes), serverless technologies, and Infrastructure as Code tools like Terraform.
• Hands-on experience with data processing frameworks (e.g., Spark) and workflow orchestration tools (e.g., Airflow).
• Deep understanding of CI/CD workflows, version control systems (e.g., Git), and modern monitoring/logging stacks (e.g., Prometheus, Grafana, ELK).