AI Infrastructure Lead (AU)

About the role

We are seeking an AI Infrastructure Team Lead to guide the team, drive long‑term direction, and continuously increase the efficiency and delivery capability of our AI organisation. This role focuses on coordinating work across the team, removing blockers, improving execution, and ensuring the AI Infrastructure group operates smoothly and effectively day to day.

You will work closely with the existing Principal Engineer, who provides deep technical leadership and architectural authority. Your role complements this by leading the people, priorities, planning, and delivery rhythms of the team. You will be responsible for creating clarity, maintaining momentum, and proactively improving how the team works, collaborates, and ships infrastructure capabilities.

A key part of this role is cross‑team alignment. You will coordinate closely with the various AI Teams, Data Engineering, and Data Capture & Delivery groups to ensure dependencies are managed, priorities are understood, and the broader AI organisation can move quickly and reliably on top of the platform.

While this is a leadership‑focused role, it remains hands‑on. You will contribute technically where needed, shape longer‑term improvements to the platform, and help drive initiatives that uplift our reliability, automation, performance, and support for AI development workflows. Your work will directly enable DroneShield’s high‑performance ML systems, distributed data pipelines, and real‑time AI workloads.

This position will report to the Director AI Systems & Platforms.

Responsibilities, Duties and Expectations

• Coordinate and lead the AI Infrastructure team’s planning, priorities, and daily operations, ensuring clear direction, strong execution, and smooth delivery across all workstreams
• Work closely with the Team’s Principal Engineer to translate long‑term architectural direction into actionable plans and well‑executed delivery
• Improve and scale the team’s ability to deliver reliable, high‑performance infrastructure for AI, data engineering, and data capture workloads
• Proactively identify blockers, gaps, and inefficiencies across the team and implement systems, processes, and practices that improve velocity and operational quality
• Drive alignment and coordination across AI Teams, Data Engineering, and Data Capture & Delivery to ensure dependencies, handoffs, and priorities are well‑managed
• Contribute hands‑on when needed to guide initiatives, validate design approaches, and support complex technical efforts
• Support the ongoing improvement of MLOps, automation, observability, and platform reliability
• Mentor and coach engineers, uphold best practices, and help build a high‑performing, collaborative team culture

Qualifications, Experience and Skills

• Degree in Computer Science, Software Engineering, or related technical discipline, or equivalent practical experience
• 7+ years in infrastructure, SRE, platform engineering, or AI/ML infrastructure roles, including experience leading engineering teams
• Strong understanding of Kubernetes environments and Linux‑based infrastructure operations (CKA/CKS a strong plus)
• Solid knowledge of Linux internals, networking concepts, performance fundamentals, and automation practices
• Experience contributing to or overseeing infrastructure for high‑performance compute environments (GPUs, storage systems, or distributed compute)
• Familiarity and experience with DevOps practices, CI/CD pipelines (GitLab preferred) and Infrastructure as Code tooling
• Experience with configuration management (Ansible, Puppet or Chef for example) and modern automation practices
• Strong understanding of distributed systems, networking, security principles, and scalable architecture patterns

Who you are

• A systems thinker who understands how to build and maintain scalable, reliable infrastructure to support demanding AI workloads.
• Skilled at balancing hands‑on contribution with leadership, coordination, and team enablement.
• Passionate about improving how teams work - increasing clarity, efficiency, and delivery capability across the organisation.
• Comfortable working across multiple technical domains and aligning engineering teams with shared goals.
• Curious, proactive, and motivated to drive continuous improvement in both technology and team operations.
• Energised by working at the intersection of AI, defence, distributed systems, and real‑world mission‑critical impact.

Note for recruitment agencies: We do not accept unsolicited candidates from external recruiters unless specifically instructed.

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