Principal Backend Developer

2 days ago


Melbourne, Victoria, Australia beBeeEngineer Full time $124,510 - $164,720
Job Description

Seeking a Senior Engineer to play a pivotal role in building self-service AI platforms. These platforms support critical capabilities such as LLM enrichment pipelines, AI gateway management, LLM serving, fine-tuning pipelines, and observability for AI workloads.

This is a high-impact role ideal for experienced engineers with a deep background in designing, leading, and delivering complex distributed systems. You'll need strong software engineering and coding skills, with bonus points for expertise in DevOps practices, infrastructure-as-code (particularly with Terraform), Kubernetes, and containerised applications.

Responsibilities:

  • Design, build, test, deploy, and maintain scalable and reliable software aligned with our technology strategy.
  • Champion engineering excellence, reliability, and performance across the AI platform.
  • Partner with the team to design and implement robust, consistent systems.
  • Troubleshoot and resolve production issues, including participation in on-call and operational support.
  • Support onboarding, mentor team members, and foster a collaborative and inclusive team environment.
  • Contribute to a positive team culture focused on safety, well-being, open feedback, and continuous growth.
Required Skills and Qualifications

Skills and experience: Technical Skills,
• Proven years of proficiency in backend development with strong experience in Java and Python.
• Deep understanding of AWS and modern cloud infrastructure.
• Skilled in writing and maintaining comprehensive unit and integration tests.
• Experienced in implementing observability and monitoring across distributed systems.
• Strong background in DevOps practices and infrastructure as code using Terraform.
• Solid understanding of system and network architecture, including identification of potential failure points.

Benefits

Nice to have:
• Exposure to full-stack development, including front-end technologies.
• Familiarity with ML tooling (e.g., KServe, Ray, vLLM, MLflow).
• Experience running and managing production applications on Kubernetes.
• Understanding of security best practices for application and infrastructure development



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