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DevOps Engineer

Sydney, NSW

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The DevOps Engineer is accountable for identifying repetitive, manual, and time-intensive tasks across L1, L2, and L3 service delivery workflows and eliminating them through automation. The role owns the discovery, design, build, deployment, and ongoing support of scripts, integrations, AI-assisted automations and CI/CD pipelines that reduce engineer toil and improve the consistency and speed of managed services delivery. The role embeds with L1, L2, and L3 analysts to understand operational workflows, prioritises automation candidates by delivery impact, and delivers well-documented automations that receiving teams can adopt, trust, and extend. The role reports to the Tools and Automation Lead.

Success in this role requires technical capability across scripting and integration, structured workflow analysis to identify and prioritise automation candidates, disciplined delivery practices grounded in peer review, documentation, and validated adoption by receiving teams, strong written communication so other engineers can adopt and maintain delivered work, and a service mindset that measures success by adoption and operational impact within delivery teams.

Key Accountabilities

Automation Backlog and Delivery

The automation backlog reflects current operational reality across L1, L2, and L3, drawing both from team-submitted requests and from first-hand observation of high-frequency workflows including alert triage, ticket enrichment, evidence collection, routine remediation, reporting,



and onboarding tasks.

Submitted automation requests arrive in the active backlog as scoped, well-defined work items with clear acceptance criteria, refined collaboratively with the requesting team lead or engineer.

Candidate automations are prioritised by measurable delivery impact (time saved, frequency, error reduction) rather than personal preference or recency bias.

Backlog priorities remain current and trusted by delivery teams through regular reprioritisation with the Tools and Automation Lead, based on impact, urgency, dependencies, and team feedback.

Automation Delivery

- Automations are delivered to production using the right tool for the job — scripting (PowerShell, Python, Bash) where logic and control matter, low-code or iPaaS where speed and maintainability dominate, and AI/LLM-driven approaches (including agentic and prompt-based patterns) where the task involves unstructured input, classification, summarisation, or natural language.
- Delivered automations are durable engineering artefacts - versioned in Git, peer-reviewed, and structured so other engineers can read, run, and extend them.
- Production delivery is iterative - usable capability is shipped early, validated against real operational use,



and refined from receiving-team feedback rather than predicted requirements
- The SIEM, ticketing, ITSM, monitoring, and Microsoft 365 / Azure / security tooling stack operates as a connected platform, with integrations that move data, trigger workflows, and reduce manual handoffs between systems.
- Internal tooling and infrastructure-as-code is delivered through repeatable, controlled CI/CD pipelines that engineers can trust for both routine and time-sensitive changes.
- Secure-by-design engineering is non-negotiable — secrets are managed correctly, credentials are scoped to least privilege, and integrations cannot be weaponised against the systems they connect.

Adoption and Production Reliability

- Delivery teams are able to adopt, run, and modify every deployed automation without dependence on the original author.
- Automations are implemented as supported capabilities, not imposed change - context, walkthroughs, and adoption support precede every deployment.
- Knowledge transfer is consistent - handover artefacts and runbooks remain accurate, current, and trusted as the underlying tools and workflows evolve.
- Production automations are observable - failures are detected and resolved by the function, not by the delivery teams that depend on them.
- Production automations remain fit for purpose as workflows evolve, with iteration driven by operational telemetry and structured feedback rather than assumption.
- Owned automations contribute to, rather than detract from, the reliability and SLA performance of the receiving service delivery teams.

Personal Performance & Skilled Standards

- Maintain and grow specialist technical capa

📌 Automation DevOps Engineer for MSPs (Australia)
🏢 Infotrust (AU)
📍 Australia