Systems Engineer - AI Safety and Tooling

4 дн. назад

AustraliaWorldwide

containerizationvirtualizationsaasinfrastructuresecurity

Build and operate infrastructure for AI-powered engineering, integrating AI SaaS, managing containerization and virtualization, and enhancing security.

О компании

is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

Обязанности

Integrate, deploy, and operate AI SaaS offerings and self-hosted AI services, collaborating cross-functionally to deliver new tools and capabilities to our tech teams.
Design and maintain the containerization and virtualization environments in which AI agents, MCP servers, and supporting services run, ensuring they are isolated, reproducible, and scalable.
Drive security hardening of AI agents and the internal services exposed to them: secrets management, access controls, sandboxing, network policy, and auditability of agent actions.
Write and maintain code to extend, integrate, and automate the services we support, from API integrations to internal tooling and automation frameworks.
Build the telemetry, monitoring, and evaluation infrastructure needed to make AI-driven workflows reliable, observable, and safe to run against production-critical systems.
Partner with development teams to align platform capabilities with their evolving AI workflows, and act as the regional point of contact for global AI platform and infrastructure collaboration.
Diagnose and resolve incidents swiftly, working with regional peers in a 'follow the sun' model to guarantee continuous system availability.

Другое

The Development Platform organization at Trading is focused on accelerating tech team workflows by providing self-service tools, services, documentation, and support. We design, build, and maintain the platforms that 's software development lifecycle depends on, establishing a consistent technical foundation across regions and empowering teams to innovate efficiently.
is embedding agentic AI directly into the developer workflow for our production-critical systems. The Development Platform team operates the infrastructure that makes this possible: the environments where AI agents run, the integrations that connect them to our systems, and the safety and security controls that keep them reliable and auditable.
We are seeking a versatile Systems Engineer to build and operate the infrastructure behind 's AI-powered engineering initiative. You will integrate AI SaaS offerings, run the containerization and virtualization layers that AI agents depend on, and harden the security of agents and the internal services they interact with. As AI adoption across our tech teams grows, so does the need for robust, secure, and observable infrastructure around it.
Based in Sydney, you will be the local point of contact for our global AI platform and infrastructure teams, collaborating closely with them while supporting the development teams who consume these capabilities every day.
3+ years of work experience in a relevant role
Bachelor's Degree in Computer Engineering, Computer Science or equivalent
Strong programming experience in Python or Go; Shell scripting is a plus.
Strong knowledge of Linux/Unix Systems
Hands-on experience with containerization and virtualization technologies, including Kubernetes and Docker.
Experience integrating and operating third-party SaaS solutions, both on-premises and leveraging AWS cloud services.
Understanding of security principles and best practices, including secrets management, sandboxing, and compliance frameworks.
Experience designing disaster recovery plans, high availability (HA) configurations, and failover strategies.
Experience with CI/CD tools such as Jenkins, GitLab CI, or TeamCity, including the automation of build, test, and deployment processes.
Curiosity and eagerness to learn about AI/LLM application patterns, even if you haven't worked closely with them yet; exposure to agentic AI tools and workflows (e.g., coding agents, MCP servers) or model-serving and evaluation infrastructure is a plus.