Cloud & AI Platform Engineer at Fortescue Metals Group
Perth, Western Australia, Australia -
Full Time


Start Date

Immediate

Expiry Date

29 Aug, 25

Salary

0.0

Posted On

29 May, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, Automation, Scripting

Industry

Information Technology/IT

Description

ABOUT US

Be part of something big. Fortescue is leading the world with our plan to decarbonise our iron ore operations, projects that harness renewable energy and the development of technology that will change our planet forever.

QUALIFICATIONS AND EXPERIENCE

  • Solid hands‑on experience with AWS services such as Lambda, ECS/EKS, S3, IAM and VPC networking
  • Experience with Python for scripting, automation or application development
  • Production exposure to Apache Airflow or Dagster (or a similar orchestrator) for scheduling and monitoring workflows
  • Confidence setting up CI/CD pipelines in GitHub Actions or comparable tooling
  • Comfort writing and refactoring Terraform (or other IaC) modules - managing multi‑environment state and safe roll‑outs
  • Familiarity with modern GenAI / LLM stacks (e.g., OpenAI, Bedrock) including prompt design and vector search concepts
  • Relevant tertiary qualifications or equivalent practical experience.
Responsibilities
  • Own and evolve the code‑base (predominantly Python) enabling AI functionality at Fortescue, setting coding standards and merging the (rare) hot‑fix quickly and safely.
  • Support architecture decisions to strategically integrate new technologies into Fortescue’s tech stack.
  • Define patterns for integrating new tools, APIs and enterprise systems and reviewing cyber compliance.
  • Design and maintain AWS infrastructure‑as‑code, extending Terraform modules to keep environments secure, scalable and cost‑efficient.
  • Automate CI/CD pipelines (GitHub Actions) to test, containerise and deploy code, and implement end‑to‑end production monitoring with alerting, logging and incident‑response playbooks
  • Lead LLM best-practice: prompt engineering, embeddings, cost-control guard-rails and safe model usage.
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