Senior Software Engineer at Squiz
Victoria, Victoria, Australia -
Full Time


Start Date

Immediate

Expiry Date

16 Dec, 26

Salary

60000.0

Posted On

17 Sep, 26

Experience

14 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Industry

Information Technology & Services

Description
  • We believe senior engineers do their best work when given real technical autonomy, deep ownership over system architecture, and space to focus on the craft of software engineering. In this role, you will work in tight lockstep with a dedicated Tech Lead and Engineering Manager, driving high-impact backend services and shaping our next-generation conversational platform. You'll be surrounded by collaborative, high-performing peers, solve complex distributed systems challenges at scale, and directly influence how enterprise customers interact with AI, all within a high-trust, flexible environment that balances rapid product delivery with sound architectural rigor.This is a permanent position open to anyone living on the east coast of Australia. We operate on a flexible, hybrid model, meaning you can balance working from home and collaborating with the team in a way that actually works for you.
Responsibilities

What the Work Looks Like Day-to-Day


  • Take ownership of core services within the Discovery team, ensuring our conversational search and content intelligence pipelines are scalable, highly available, and structurally sound
  • Design and implement resilient, decoupled distributed systems using event-driven architectures, maintaining clean API boundaries and robust fault tolerance
  • Embed DevSecOps practices within the team, integrating automated security scanning, vulnerability management, and strict IAM principles into everything we build
  • Maintain and optimize CI/CD pipelines, driving automated testing, reliable deployment strategies (like blue-green or canary releases), and infrastructure reproducibility
  • Participate in FinOps practices for our domain, monitoring and optimizing AWS infrastructure spend across compute (ECS/Fargate/Lambda), storage (S3), search indexes, and LLM usage
  • Contribute to Generative AI and RAG architectures, helping evaluate and integrate tools like AWS Bedrock safely, cost-effectively, and pragmatically
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