Top Tech Jobs & Startup Jobs in Melbourne

Lead the technical vision, security, CI/CD, data governance, monitoring, release engineering, and AI operations strategy for Xero’s enterprise Salesforce platform. The role combines hands-on Salesforce development with architecture, platform reliability, compliance, automation, and engineering enablement. Responsibilities include coaching engineers, modernizing deployment pipelines, managing platform risk and limits, overseeing D360 integrations, and establishing standards for Agentforce and AI operations.

Design, build, and operate an internal AI skills marketplace and distribution platform. Own end-to-end delivery from experimentation to production, create runbooks, monitoring, rollback plans, and provide guidance on authoring agent skills while collaborating with vendors and engineering teams.

Build and rapidly deploy internal AI-powered tools and automations that reduce operational toil. Integrate Jira, Confluence, Workday, and data warehouses through APIs; automate reporting, headcount management, and roadmapping workflows; evaluate custom, low-code, and SaaS solutions; prototype scalable AI-enabled improvements; and mentor operations teams in modern AI tooling.

Lead strategy and execution for Xero’s AI Shared Services platform, including eventing, communications, search, and related reusable capabilities. Define the domain roadmap, establish success metrics and dashboards, build stakeholder relationships, and drive adoption across product and engineering teams. The role requires managing interdependent platform products, applying technical fluency across distributed systems and cloud environments, making investment cases, navigating ambiguity and dependencies, and growing high-performing people and teams.

Lead the strategy, development, and scaling of shared platforms and operating models for AI-native delivery. Align stakeholders, establish roadmaps and governance, measure adoption and organizational impact, and move AI workflows from pilots into repeatable products. Partner with Engineering, Security, Data, and other teams while coaching teams in effective AI product practices and translating complex technical capabilities into investment decisions.

Design, build, and operate production security capabilities for threat detection and response. Develop detection, monitoring, automation, and response workflows across SIEM, SOAR, EDR, and cloud security platforms. Improve detection coverage, control effectiveness, and operational reliability while applying AI safely to security engineering. Lead complex technical initiatives, collaborate across security and engineering teams, and communicate technical risks and trade-offs clearly.

Designs and operates identity and access controls across AWS, GCP, and Azure. Builds Terraform modules, policy guardrails, automation, and internal tooling to enable secure cloud access at scale. Leads technical design discussions, improves reliability, establishes IAM performance metrics, closes identity gaps, and mentors engineers. Collaborates with platform, security, and product teams to integrate secure-by-default controls and improve developer experience.

Build internal tooling and platform improvements for database reliability. Split time between software engineering and database operations: monitoring, observability, performance tuning, incident response, migration to RDS/Postgres, and automating fleet management to improve resilience and developer efficiency.

Develop and deploy machine learning products and services by translating complex business problems into applied research programs. Build robust data pipelines and reusable code in Python or Scala, develop and evaluate applications involving NLP, computer vision, and LLMs, and monitor algorithms at scale. The role also involves managing research risks, collaborating cross-functionally, mentoring colleagues, communicating complex findings, and raising scientific and engineering standards.

Lead engineering team to modernize C#/.NET and React codebases, design scalable distributed systems on cloud (AWS), integrate agentic AI/LLMs into workflows and products, improve CI/CD, reliability and incident response, mentor engineers, and drive cross-functional technical strategy.