Why this role exists:

The Associate AI Engineer sits inside a Customer Platforms and supports by orchestrating AI agents to produce code, tests, and documentation, ensuring features across Officeworks digital properties are built and maintained efficiently. The role is a full stack engineering role and bridges feature development and quality assurance by directing agent workflows and conducting critical reviews before code is committed to production.
In addition to feature development, the role contributes to the ongoing operation, maintenance, and support of Customer Platforms systems in production. This includes monitoring system performance and health, identifying and resolving production issues, supporting incident and defect resolution, and implementing fixes and enhancements to ensure the reliability, stability, and continuous improvement of digital platforms

Where you will make a difference:

In this role you will:

Agent Workstream Orchestration:

- Run single or paired agent workstreams across coding, test generation, and documentation workflows.
- Translate technical and product specifications into precise, structured instructions for AI agents to execute.
- Apply platform context, base coding standards, and security policies to every agent execution.
- Monitor parallel agent tasks and confirm that generated outputs satisfy specified functional requirements.

Code Review and Quality Assurance:

- Perform rigorous reviews of agent-generated code, automated tests, and technical documentation.
- Design and execute test cases across unit, integration, and end-to-end scenarios, extending beyond AI-generated coverage where gaps exist.
- Evaluate generated code for functional correctness, security vulnerabilities, performance, and architectural fit.
- Identify, document, and track defects to resolution, escalating severity and blockers to Senior AI Engineers where required.

Documentation and Shared Context Management:

- Maintain accurate, up-to-date documentation and knowledge artefacts to ensure context repositories effectively feed subsequent agent runs.
- Identify and resolve missing, outdated, or ambiguous context in shared repositories that negatively affects agent accuracy.
- Log technical decisions and specification updates to maintain end-to-end trace abilities for system workflows.





Operational Support and Issue Resolution:

- Support the investigation and resolution of production issues across the platform domains managed by the pod.
- Participate in on-call support rotations as required to maintain platform reliability and system availability.
- Support release verification and post-deployment checks to confirm features perform as tested before hypercare handover.
- Track runtime anomalies or recurring defects and feed learnings back into context documentation and agent guidance.

Who you will be working with:

- Pod Delivery Teams: Partner with Product Orchestrators and fellow pod engineers to translate specifications into executable agent workflows and deliver features in continuous flow.
- Platform and Architecture Specialists: Work with Context Engineers, Solution Architects, and Associate AI Agent Evaluation Engineers to align work with base contexts, security policies, and review frameworks.
- Operations and Enablement Teams: Collaborate with Platform Engineers, Associate AI Agent Operations Engineers, and the AI Enablement Manager to leverage shared tools, continuous integration pipelines, and observability platforms.

Vendor and External Partners: Engage with external vendor support and technology partners as directed to resolve tooling issues or platform integration requirements.

What success looks like:

- Delivery Velocity and Quality: High review pass rate on submitted code and test artefacts, with minimal defects escaping to production environments.
- Capability Progression: Demonstrated growth in independent review judgement, prompt engineering literacy, and agent orchestration.
- Artefact Currency: High accuracy and completeness of shared context repositories and technical documentation contributed to the pod.
- Operational Resilience: Timely response to and resolution of domain incidents, maintaining reliable and secure platform performance.
- 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 robust 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

Qualifications and work experience:

Essential:

- Education: Tertiary degree in Computer Science, Software Engineering, or a related field.
- Experience: 3+ years of software engineering experience, with exposure to full-stack delivery, cloud-based systems, and hands-on software testing or quality assurance.
- Tooling Literacy: Practical experience utilising AI-assisted coding and agent tools (e.g., Claude Code, Git Hub Copilot, Codex) to build and test software.
- Full Stack Capability: Foundational knowledge across front-end, back-end, and integration technologies (e.g., Java Script/Type Script, Node.js, React, REST APIs).
- Quality Engineering: Hands-on experience designing and executing test cases (unit, integration and end-to-end) and documenting defects to resolution, not just familiarity with testing principles.
- Software Quality: Understanding of software testing principles, including automated unit, integration, and end-to-end testing practices.
- Specification and Logic: Ability to interpret functional specifications, construct precise logic instructions, and review generated code for correctness.
- Collaboration and Process: Familiarity with modern continuous integration and delivery pipelines (CI/CD), Git version control, and continuous flow delivery models.

Preferred:

- Retail and Commerce Exposure: Familiarity with modern omnichannel commerce platforms or digital retail environments.
- Observability Frameworks: Exposure to cloud logging and observability tooling such as Sumo Logic or Datadog.
- Cloud Technologies: Basic exposure to Amazon Web Services (AWS) or serverless cloud architecture patterns.

📌 Associate AI Engineer (India)
🏢 Officeworks
📍 India