Why this role exists:

The Senior AI Engineer sits inside a Customer Platforms pod and orchestrates the technical agents that produce code, tests, documentation and design artefacts. The role is a full stack engineering role that takes complete ownership of the quality engineering and testing, holding accountability for everything committed to production.

The role exists to translate product specifications into functional agent tasks, maintain the human-in-the-loop review gate, and ensure system design integrity, non-functional performance and security standards are met. It plays a critical role in enabling continuous delivery across Customer Platforms while mentoring junior engineers and continuously improving agent workflows across pods.

Where you will make a difference:

In this role you will:

Agent Orchestration and Execution:

- Decompose Product Orchestrator specifications into functional tasks for technical agents.
- Run multiple agents in parallel across coding, test generation, documentation and design workflows.
- Sequence workstreams and manage technical dependencies to maintain high pod delivery velocity.
- Apply base context, security policies and platform standards to every agent execution cycle.

Quality Control and Commit Gate:

- Hold the human-in-the-loop review and commit gate independently on complex and high-risk change.
- Perform fast, accurate code and test reviews to ensure correctness, specification alignment and standards conformance.
- Owns end-to-end quality assurance accountability by designing agent test coverage and evaluation logic.
- Own defect management for the pod, from identification through root cause and resolution tracking, escalating systemic quality risks.
- Identify when agent workflows are insufficient and apply direct engineering intervention to resolve technical issues.

System Design and Non-Functional Excellence:

- Own architectural fit and system design judgement across the features delivered by the pod.
- Ensure non-functional outcomes, including performance, scalability, resilience and security, are met across all releases.
- Lead production incident resolution within the pod across touched platform domains.
- Contribute to domain design decisions as a consulted partner to the Solution Architects.

Knowledge Governance and Workflow Improvement:

- Maintain accurate, up-to-date documentation and knowledge artefacts to serve as context layers for future agent runs.
- Feed refined domain context back to central repositories in collaboration with Context Engineers.
- Continuously refine and optimise agent workflows and share best practices across engineering pods.




- Mentor engineers on test design, defect triage and quality engineering practice across the pod.

Who you will be working with:

- Pod Leadership and Delivery Teams: Partner with Product Orchestrators and fellow pod engineers to refine requirements, assess technical feasibility and execute workstreams.
- Architecture Teams: Consult with Domain Architects and Solution Architects on domain design, system architecture and escalation pathways.
- Capability and Platform Specialists: Collaborate with Context Engineers, Associate AI Agent Evaluation Engineers and Associate Platform Engineers to align on shared context, security standards and tooling.
- Vendor and Platform Partners: Liaise with external AI tooling providers and vendor technical support to resolve complex platform constraints and adopt new capabilities.

What success looks like:

- Commit Gate Integrity: Low commit gate escape rate on complex and high-risk production changes.
- Innovation and Scaling: Agent workflow improvements developed within the pod are successfully adopted across broader engineering teams.
- Operational Resilience: Rapid resolution of production incidents within the pod with minimal downtime or customer impact.
- Delivery Velocity: High throughput of automated coding and testing tasks achieved without compromising technical quality or architectural standards.
- Demonstrates behaviours aligned to Officeworks values, contributing to a respectful, inclusive and high-performing culture.

How you will lead:

Individual Contributor

- Lives our Officeworks values and behaviours
- Proactively contributes to a safe working environment, escalates appropriately if there are unsafe conditions or inappropriate behaviour
- Operates in line with applicable Officeworks company policies and Code of Conduct
- Demonstrates a strong sense of personal accountability and curiosity to learn and develop
- Contributes to an inclusive and respectful environment where diverse perspectives are valued and everyone feels safe to speak up and belong

Our Values:

Our values shape the way we work, our behaviours and how we interact with each other, our customers, suppliers and communities.

We begin with customer:

- We start with our customer needs in every decision.
- We offer simple,



helpful and affordable solutions.
- We listen, learn and continuously improve.

We do the right thing:

- We lead with integrity and care for our team communities and planet.
- We work together safely and treat everyone with respect, inclusion, and trust.
- We collaborate across teams and think Officeworks-wide.

We execute with accountability:

- We are accountable for our decisions, actions, results, and mistakes.
- We stay across the details and focus on delivering what matters.
- We move with pace and agility to deliver outcomes.

We lead with ambition:

- We set bold ambitions that help us to win and transform.
- We are courageous with current ideas.
- We focus on transformation, not incremental steps.

Qualifications and work experience:

Essential:

- Education: Tertiary degree in Computer Science, Software Engineering, or a related field.
- Experience: 8-10 years of software engineering experience, primarily full stack with microservices architecture exposure, including senior-level ownership of quality engineering and test strategy.
- AI-Assisted Delivery: Proven experience or strong proficiency in delivering production software using AI coding, test generation and orchestration tooling.
- Quality Ownership: Demonstrated track record of owning end-to-end code quality, test strategy design, defect management and release gates directly, built through hands-on quality engineering experience.
- Stack Breadth: Broad technical exposure across front-end, back-end and integration layers.
- System Design: Strong system design judgement with the capability to evaluate, challenge and refine agent-generated architectural outputs.
- Technical Support: Experience supporting production cloud environments, including logging, alerting, incident response and observability
- Proficient in Kotlin, with a strong understanding of Jetpack Compose, View-based layouts (XML), , Kotlin Flows, Coroutines and asynchronous programming (async/await, structured concurrency).
- Solid grasp of MVVM architecture, Clean Architecture patterns (Use Cases / Repositories), and Navigation Component.
- Experienced in unit and UI testing using JUnit, Mock, and Espresso / Compose Test frameworks.
- Hands-on experience with CI/CD pipelines, preferably Bitrise.
- Experienced in managing dependencies using Gradle (Kotlin DSL / Version Catalogs).

Preferred:

- Retail and Commerce Exposure: Experience in retail, e-commerce, or complex omnichannel platform ecosystems.
- Advanced AI Tooling: Familiarity with up-to-date AI agent frameworks, model gateways, and evaluation platforms.

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