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 developersto 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).