Systems Engineer - AI Safety and Tooling
- Build and operate internal services, automation and integrations using Python and/or Go.
- Design and maintain containerised and virtualised environments across Kubernetes, Docker and AWS.
- Implement security controls around secrets, access, isolation, network policy and auditability.
Systems Engineer - AI Safety & Tooling
Sydney | Global trading firm | High-impact developer platform role
We're partnering with a leading global trading firm to find a Systems Engineer for a newly forming team at the intersection of platform engineering, developer productivity and AI safety.
This is not a role building or training AI models. Instead, you'll build and operate the secure, reliable infrastructure that enables engineering teams to use AI-powered tools and coding agents safely within production-critical environments.
You'll work on the environments where these tools run, the integrations that connect them to internal systems, and the operational controls that make their use observable, auditable and resilient.
What you'll be doing
Build and operate internal services, automation and integrations using Python and/or Go
Design and maintain containerised and virtualised environments across Kubernetes, Docker and AWS
Enable AI SaaS and self-hosted services for engineering teams, with a focus on reliability and operational safety
Implement security controls around secrets, access, isolation, network policy and auditability
Improve telemetry, monitoring and evaluation capabilities for AI-enabled engineering workflows
Investigate incidents, reduce operational toil and raise the standard for how the platform is run
Partner with engineering, security, cloud and infrastructure teams globally to deliver new platform capabilities
What we're looking for
This will suit a software-first platform, SRE or systems engineer who enjoys building tools that other engineers depend on.
You'll bring:
Strong hands-on coding ability in Python or Go, with examples of production software, services, tools or automation you have personally designed and shipped
Deep Linux/Unix fundamentals and experience operating production infrastructure
Strong Kubernetes and Docker experience in a live environment-not just deployment or configuration exposure
Experience with observability, incident response, alerting and improving the reliability of systems others rely on
Exposure to cloud services, CI/CD, API integrations and secrets/access management
A proactive mindset: comfortable solving ambiguous problems, creating structure and taking ownership from discovery through to implementation
Genuine curiosity about AI tooling, agentic workflows and how to introduce them safely into engineering environments
Experience with MCP servers, coding agents, API gateways, service mesh, sandboxing, gVisor, Firecracker, isolated CI runners or untrusted-code execution would be highly regarded, but is not essential.
Why this opportunity?
You'll join a high-performing global technology organisation at an early and influential point in the build-out of its AI-powered engineering capability. The work is meaningful, technically challenging and highly visible-giving you the chance to shape how developers safely use emerging AI tools across a production-critical environment.
The role is Sydney-based and will be mostly office-based during the first year.
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Skills
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