Associate, Platform Engineer

Job Summary

Enterprise AI s platform team needs engineers who are learning the trade in a production AI setting. The Associate Platform Engineer builds the pipeline of platform engineering capability the team needs as its portfolio grows.

Responsibilities

• Delivers defined platform tasks under direction from senior engineers, contributing to the health and quality of the platform estate.
• Builds AI-native fluency from the start. AI coding assistants are the default mode of work, not an occasional aid.
• Grows into full Platform Engineer responsibility with active support and mentorship from the Lead and Senior Platform Engineers.
• Maintain runbooks, FAQs, and onboarding materials for the platforms, contributing to institutional knowledge.
• Apply established platform standards and patterns; flag inconsistencies to senior engineers.

Learning & Development

• Build familiarity with the platform estate and developer tooling stack (GitHub Copilot, Claude Code/Cowork, Codex, Databricks AI Assistant, Accelerator platform) and core Google Cloud services (IAM, Cloud Storage, BigQuery, Cloud Run, Vertex AI).
• Learn GCP security basics (IAM, Secret Manager, data access controls) and grow toward CMEK, VPC Service Controls, and GxP awareness over time.
• Actively learn from senior engineers and build the skills to grow into Platform Engineer I responsibilities.

Education

• Bachelor s degree in Computer Science, Software Engineering, or equivalent practical experience.

Required skills

• About 2 years of experience or a relevant internship in software engineering, cloud platforms, or DevOps.
• Working proficiency in Python and SQL.
• Working knowledge of at least one cloud platform (GCP preferred; Azure or AWS acceptable).
• Hands-on use of Terraform or another IaC tool, and basic CI/CD pipeline experience.
• Daily use of AI coding agents (Claude Code, Codex, GitHub Copilot, Databricks AI Assistant) as a primary development mode.

Preferred skills

• Familiarity with GitOps, container tooling (Docker, Cloud Run or GKE), or CI/CD pipelines.
• Coursework or projects involving AI/ML systems or LLM applications.
• Exposure to BigQuery, Vertex AI, or Databricks through a project, internship, or coursework.
• Foundational cloud certification (Google Cloud Digital Leader, Associate Cloud Engineer, Azure Fundamentals, or similar).

Skills

• Data Integration
• Docker Container
• ETL Development
• Performance Tuning
• SQL
• Vertex AI

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.